Enhancing Health and Sports Performance by Design: Proceedings of the 2019 Movement, Health & Exercise (MoHE) and International Sports Science Conference (ISSC) (Lecture Notes in Bioengineering) 9811532699, 9789811532696
This book gathers papers presented at the 2019 Movement, Health & Exercise (MoHE) Conference and International Sport
118 47 30MB
English Pages 564 [550] Year 2020
Preface
Organizing Committee
Chairman
Deputy Chairman
Logistics
Website and Publication
Scientific Committee
Contents
Exercise Science
Determination of Cardiac Function Using Impedance Cardiography During Jogging With and Without Breast Support
Abstract
1 Introduction
2 Materials and Methods
2.1 Participants
2.2 Experimental Procedures
2.3 Statistical Analysis
3 Results
3.1 General Characteristics
3.2 Resting Cardiac Variables
3.3 Changes in Metabolic Variables During Exercise
3.4 Changes in Cardiac Variables During Exercise
3.5 Changes in Respiratory Variables During Exercise
4 Discussion
5 Conclusion
References
Changes in Immune Response to Moderate Exercise in Active Trainees
Abstract
1 Introduction
2 Materials and Methods
2.1 Study Area and Subjects
2.2 Physical Activity Programme
2.3 Experimental Design
2.4 Variables Studied
2.5 Ethical Consideration
2.6 Statistical Analysis
3 Results
4 Discussion
5 Conclusion
Acknowledgements
References
Effects of Attentional Focus Among Novices and Elite Athletes in Sprinting Performance
Abstract
1 Introduction
2 Method
2.1 Participants
2.2 Instruments
2.3 Procedure
3 Result
4 Discussion
5 Conclusion
References
The Effects of Myofascial Release Using Foam Rolling and Resistance Band Assisted Stretching on Malaysian Rugby Players’ Lower Body Power and Flexibility
Abstract
1 Introduction
2 Methods
2.1 Experimental Design
2.2 Participants
2.3 Protocol and Measurement
2.4 Statistical Analysis
3 Results
4 Discussion
References
The Effects of High Intensity Functional Interval Training on Selected Fitness Components Among Young Badminton Players
Abstract
1 Introduction
2 Methods
2.1 Experimental Approach to the Problem
2.2 Participants
2.3 Procedures
2.4 Statistical Analysis
3 Results
4 Discussions
4.1 Effect of High Intensity Interval Functional Training on Aerobic Fitness
4.2 Effect of High Intensity Interval Functional Training on Agility
4.3 Effect of High Intensity Interval Functional Training on Sprint
5 Conclusion
Acknowledgements
References
The Effect of Amplitude (Response Complexity) in Choice Reaction Time
Abstract
1 Introduction
2 Method
2.1 Participants
2.2 Apparatus
2.3 Task and Procedure
3 Results
3.1 Reaction Time (RT)
3.2 Movement Time to the First Target (MT1)
4 Discussion
5 Conclusion
References
Effect of Medial Longitudinal Arch Height on Static and Dynamic Balance Among UiTM Female Athletes
Abstract
1 Introduction
2 Methods
2.1 Participants
2.2 Instrumentation
2.3 Procedures
3 Results
4 Discussion
5 Conclusion
6 Recommendation
References
The Relative Age Effect in Malaysia Youth Athletes
Abstract
1 Introduction
2 Method
2.1 Research Design
2.2 Participants
2.3 Procedure
2.4 Statistical Analyses
3 Result
4 Discussion
5 Conclusion
6 Recommendation
References
Human Performance
The Acute Effects of Exercises Order During Upper-Lower Body Alternated Supersets Among Trained Men
Abstract
1 Introduction
2 Methodology
2.1 Participants
2.2 Squat and Bench Press Procedure
2.3 EMG Procedure
2.4 Data Analysis
3 Results
3.1 Comparison of Muscles Activation Between the Exercises Order
3.2 Number of Repetitions Completed Between Exercises Order
4 Discussions
5 Conclusions
References
Body Composition and Muscular Performance of Malaysian Young Male State Level Weightlifting, Cycling and Squash Athletes
Abstract
1 Introduction
2 Methodology
2.1 Participants’ Recruitment
2.2 Experimental Design
2.2.1 Body Composition, Resting Heart Rate and Blood Pressure Measurements
2.2.2 Handgrip Strength, and Back and Leg Strength Measurements
2.3 Data Analysis
3 Results
4 Discussion
Competing Interests
References
Development of a Soccer-Specific Running Protocol for Young Soccer Players
Abstract
1 Introduction
2 Materials and Methods
2.1 Subjects
2.2 Familiarisation
2.3 Match Analysis Data
2.4 Experimental Design
2.5 SSP Speed
2.6 SSP Protocol
3 Statistical Analysis
4 Results
4.1 Body Mass and Urine Specific Gravity (USG)
4.2 Perceptual Scales
4.3 Countermovement Jump
4.4 Peak Sprint Speed
4.5 Heart Rate
5 Discussion
Acknowledgements
References
The Potentiating Effects of an Eccentric Load on Horizontal Jumps Among Handball Players
Abstract
1 Introduction
2 Method
2.1 Subjects
2.2 Procedures
2.3 Measurements
2.3.1 1RM Protocol
2.3.2 Standing Broad Jumps
2.3.3 105% and 125% of 1RM Leg Press
2.4 Statistical Analysis
3 Result
4 Discussion
5 Practical Application
References
The Confirmatory Factor Analysis of the Malay Language Revised Competitive State Anxiety Inventory-2 (CSAI-2R) Among Adolescent Malaysian State Level Athletes
Abstract
1 Introduction
2 Methods
2.1 Participants
2.2 Questionnaire Translation
2.3 Data Collection
2.4 Measures
2.5 Ethics Approval
2.6 Statistical Analysis
3 Results
3.1 Measurement Model CSAI-2R Malay Version
3.2 Internal Consistency
4 Discussion
5 Conclusion
References
Conventional Jump Warm-Up with and Without Jumping Rope on Jumping Ability Among Volleyball Players
Abstract
1 Introduction
2 Methods
2.1 Participants
2.2 Material
2.3 Design
2.4 Procedures
3 Results
4 Discussion
5 Conclusion
6 Practical Implication
References
Identification of Running, Jogging and Walking Activities for Female Athletes Indoor Hockey in 2016 PON Matches
Abstract
1 Introduction
1.1 A Subsection Sample
2 Methods
2.1 Participants
2.2 Match Analysis
3 Results
3.1 Running Activities
3.2 Jogging Activities
3.3 Walking Activities
4 Conclusion
References
Carbohydrate Mouth Rinsing in Thermoneutral Enhances Prolonged Running Performance Compared to Hot-Humid Environment
Abstract
1 Introduction
2 Materials and Method
3 Results
4 Discussion
References
Which Joint Angle Changes Have Most Influence on Dart Release Speed?
Abstract
1 Introduction
2 Methodology
2.1 Experiment
2.2 Simulation Model
3 Results
3.1 Model Evaluation
3.2 Simulation
4 Discussion and Conclusion
References
The Influence of Anthropometrics, Physical Fitness, and Technical Skill on Performance of U-12 Youth Soccer Players in Malaysia
Abstract
1 Introduction
2 Material and Method
2.1 Participants
2.2 Anthropometrics
2.3 Soccer Battery Test
2.4 Soccer Technical/Specific Skills
2.5 Data Analysis
3 Result and Discussion
4 Conclusion
Acknowledgment
References
Management and Sports Studies
Identifying Element of Academic Enhancement Support for Student-Athlete Using Fuzzy Delphi Method
Abstract
1 Introduction
2 Literature Review
3 Methodology
3.1 Fuzzy Delphi Technique
3.2 Data Analysis
4 Conclusion
References
A Review of Pathways Towards Expert Performance on Elite Youth Athletes
Abstract
1 Introduction
2 Method
3 Result
3.1 Early Specialization Pathway Towards Elite Level
3.2 Early Diversification Pathway Towards Elite Level
4 Conclusion
Funding
References
The Relationship Between Organizational Commitment and Internal Service Quality Among the Staff in Majlis Sukan Negeri-negeri in Malaysia
Abstract
1 Introduction
2 Methodology
3 Results
3.1 Organizational Commitment and Internal Service Quality of the Staff at Majlis Sukan Negeri-negeri in Malaysia
3.2 Relationship Between Organization Commitment with Internal Service Quality
4 Discussion
5 Conclusion
References
Accessibility Dimensions (Factors) of Parks and Playgrounds
Abstract
1 Introduction
1.1 Accessibility
1.2 Motivation of Attendance
2 Problem Statement
3 Research Methodology
3.1 Population and Sample
3.2 Research Instrument
4 Result
5 Discussion and Conclusion
References
Physical Activity and Health
Influence of Individual Physical Activity on EMG Muscle Activation Pattern
Abstract
1 Introduction
2 Method
2.1 Participants
2.2 Experimental Setup and Procedure
2.3 Statistical Analysis
3 Result
4 Discussion
5 Conclusion
References
Immediate Effect of Single Bout of Karate Exercise on Heart Rate
Abstract
1 Introduction
1.1 Objective of the Study
2 Materials and Methods
2.1 Study Location and Subjects
2.2 Variables Studied
2.3 Study Design
2.4 Administration of Test
2.5 Statistical Analysis
3 Result
4 Discussion
5 Conclusion
6 Recommendations
References
Incorporating Traditional Games in Physical Education Lesson to Increase Physical Activity Among Secondary School Students: A Preliminary Study
Abstract
1 Introduction
2 Methodology
2.1 Study Design and Sampling
2.2 Anthropometric Measurement
2.3 Study Protocol
2.4 Physical Activity Measurement
2.5 Ethical Issues
2.6 Statistical Analysis
3 Result
3.1 Demographic Data
3.2 Anthropometric Data
3.3 Physical Activity Data
3.4 Comparison of Physical Activity Between Gender
3.5 Comparison of Physical Activity Across BMI Categories
4 Discussion
5 Conclusion
Conflict of Interest
References
Muscle Strength in Male Youth that Play Archery During Leisure Time Activity
Abstract
1 Introduction
2 Methodology
2.1 Study Design
2.2 Body Anthropometry
2.3 Muscle Strength Assessment
2.4 Statistical Analyses
3 Results
4 Discussion
5 Conclusion
Acknowledgements
References
The Effect of Zone, Gender, RAE and Fitness Variables Towards Fitness Status and Anthropometric Attributes of Children in Malaysia
Abstract
1 Introduction
2 Material and Method
2.1 Area of Study
2.2 Participants and Testing Procedure
2.3 Statistical Analysis
3 Results and Discussion
4 Conclusion
Acknowledgments
References
Sports Engineering and Technology
Offline LabVIEW-Based EEG Signals Analysis to Detect Vehicle Driver Microsleep
Abstract
1 Introduction
1.1 Background
1.2 EEG Signals
1.3 Brain-Computer Interface (BCI)
1.4 Research Objective
2 Methodology
2.1 Subject Selection
2.2 EEG Measurement and Protocol
2.3 EEG Signal Processing
2.4 Feature Extraction
2.5 Short Time Fourier Transform (STFT)
2.6 k-NN Classification
2.7 Flowchart and Block Diagram of the Study
3 Results and Discussion
3.1 Overall LabVIEW Block Diagram
3.2 Graphical User Interface (GUI)
3.3 Analysis of Standard Deviation Value of EEG Signals
3.4 Analysis of Spectral Centroid Value of EEG Signals
3.5 Feature Classification
3.6 Spectrogram Analysis
4 Conclusion
Acknowledgement
References
Vision Based Automated Badminton Action Recognition Using the New Local Convolutional Neural Network Extractor
Abstract
1 Introduction
2 Related Works
3 Methodology
4 Results and Discussion
5 Conclusion
Acknowledgement
References
Investigation of Different Time-Series Segmented Windows from Inertial Sensor for Field Hockey Activity Recognition
Abstract
1 Introduction
1.1 Background of Study
1.2 Related Work
2 Methodology
2.1 Data Acquisition and Collection
2.2 Segmenting and Sliding of Fixed Window Size
2.3 Extraction of Fixed Features from Signal
3 Result and Discussion
4 Conclusion
Acknowledgment
References
Effect of Stroke Rate Increment on Power Output and Foot Asymmetries Force Among Malaysian University Rower
Abstract
1 Introduction
2 Methods
2.1 Participants
2.2 Protocol
2.3 Instrumentation
2.4 Data Analysis
2.5 Statistical Analysis
3 Results
4 Discussion
5 Conclusion
Acknowledgment
References
Object Detection Approach Using Single Shot Multibox Detector for Sprinting Movement Recognition
Abstract
1 Introduction
2 Single Shot Multibox Detector
3 Methodology
3.1 Motion Data Collection
3.2 Dataset Creation
3.3 Model Development of Object Detection
3.4 Evaluation of Model Development
4 Result
4.1 Test for Accuracy of Object Detection
4.2 Sprinting Detection Model Framework
4.3 Sprinting Detection Against Time
5 Discussion
6 Conclusion
Acknowledgment
References
Physical Fatigue Prediction Based on Heart Rate Variability (HRV) Features in Time and Frequency Domains Using Artificial Neural Networks Model During Exercise
Abstract
1 Introduction
2 Method
2.1 Subjects
2.2 Experimental Protocol
2.3 Signal Processing and Feature Extraction
2.4 Machine Learning
3 Results and Discussion
4 Conclusion
Acknowledgement
References
The Effect of Compression Socks on Running Kinematics in Experience and Novice Runners
Abstract
1 Introduction
2 Materials and Method
2.1 Participants
2.2 Bruce Protocol
2.3 Running Kinematics Analysis
2.4 Procedures
3 Data Analysis
4 Results
4.1 Ground Contact Time
4.2 Swing Time
4.3 Stride Length
4.4 Heel Strike
5 Discussions
5.1 Ground Contact Time
5.2 Swing Time
5.3 Stride Length
5.4 Heel Strike
6 Conclusions
Acknowledgements
References
The Classification of Skateboarding Trick Manoeuvres: A K-Nearest Neighbour Approach
Abstract
1 Introduction
2 Methods
2.1 Instrumented IMU Device
2.2 Data Collection
2.3 Machine Learning
3 Results and Discussion
4 Conclusion
Acknowledgement
References
The Application of Artificial Neural Networks in Predicting Blood Pressure Levels of Youth Archers by Means of Anthropometric Indexes
Abstract
1 Introduction
2 Methodology
2.1 Participants
2.2 Anthropometrics Measurements
2.3 Blood Pressure Measurement
3 Data Analysis
3.1 Development of ANN Model
3.2 Development of MLR Model
3.3 Model Evaluation
4 Results and Discussion
5 Conclusion
Acknowledgement
References
Sports Medicine
Prevalence of Cardiovascular Risk Factors Among Professional Football Athletes in Sabah, Malaysia
Abstract
1 Introduction
2 Materials and Method
2.1 Study Design
2.2 Participant
2.3 Clinical Evaluation
2.4 Statistical Analysis
3 Results
4 Discussion
5 Conclusion
Conflict of Interest
References
External Snapping Hip Syndrome: A Case Report of a Professional Hockey Player
Abstract
1 Introduction
1.1 Case Report
1.2 Functional Status
1.3 Physical Examination and Investigation
1.4 Follow up Treatment
2 Discussion
3 Conclusion
References
Ouch! My Hip Hurts: A Rare Case Report of Rectus Femoris Muscle Tear Causing Failure in Hip Extension
Abstract
1 Introduction
2 Case Presentation
3 Investigation
4 Treatment
5 Outcome and Follow up
6 Discussion
7 Conclusion
References
Sports Nutrition
A Randomized Controlled Trial of the Effects of Dietary Nitrate Supplementation on Blood Pressure, Exhaled Nitric Oxide Level and Maximal Isometric Handgrip Strength in Pre-hypertensive Women
Abstract
1 Introduction
2 Methodology
2.1 Subjects
2.2 Experimental Protocol
2.3 Measurements
2.4 Statistical Analysis
3 Results
3.1 Blood Pressure Indices
3.2 Fractional Exhaled Nitric Oxide (FeNO)
3.3 Maximal Voluntary Isometric Contractions
4 Discussion
5 Conclusion
Acknowledgement
References
The Effect of Various Carbohydrate Concentrations Mouth Rinsing on Intermittent Running Performance
Abstract
1 Introduction
1.1 CHO Mouth Rinse
2 Methodology
2.1 Subjects
2.2 Experimental Protocol
2.3 Yo-Yo Intermittent Recovery Test Level 1 (Yo-Yo IRT-1)
2.4 Mouth Rinse Procedures
2.5 Urine Specific Gravity (USG)
2.6 Blood Glucose Concentration
2.7 Heart Rate (HR)
2.8 Subjective Rating
2.9 Statistical Analysis
3 Results
3.1 Total Distance Cover and Level of Exhaustion
3.2 Urine Specific Gravity (USG)
3.3 Blood Glucose Concentration
3.4 Heart Rate (HR)
3.5 Subjective Rating
4 Discussion
5 Conclusion
References
Nitrate-Rich Red Spinach Extract Supplementation Increases Exhaled Nitric Oxide Levels and Enhances High-Intensity Exercise Tolerance in Humans
Abstract
1 Introduction
2 Methods
2.1 Subjects
2.2 Experimental Protocol
2.3 Measurements
2.4 Statistical Analysis
3 Results
3.1 Blood Pressure
3.2 Fractional Exhaled Nitric Oxide (FeNO)
3.3 High-Intensity Exercise Tolerance
4 Discussion
5 Conclusion
Acknowledgement
References
The Role of Fitness Status in the Performance-Enhancing Effects of Dietary Inorganic Nitrate Supplementation: Meta-analysis and Meta-regression Analysis
Abstract
1 Introduction
2 Methodology
2.1 Search Strategy and Study Selection
2.2 Fitness Classification
2.3 Statistical Analysis
3 Results
3.1 Meta-analysis
3.2 Meta-regression
4 Discussion
5 Conclusion
Acknowledgement
References
An Overview of a Dietary Pattern Among Malaysian Endurance Athletes in Relation to Glycemic Index
Abstract
1 Introduction
2 Methodology
2.1 Study Design and Respondents
2.2 Instrumentation
2.3 Data Analysis
3 Results
3.1 Respondents’ Background
3.2 Anthropometric Characteristics
3.3 Major Contributors to Energy, CHO, Protein and Fat Intake
4 Discussion
5 Conclusion
References
Sports Psychology
Coach-Athlete Relationship and Coaching Effectiveness in Team Sports Athletes
Abstract
1 Introduction
1.1 Coach-Athlete Relationship
1.2 Coaching Effectiveness
1.3 Coaching Effectiveness and Coach-Athlete Relationship
1.4 Research Aims
2 Research Methodology
2.1 Participants
2.2 Instrumentation
2.3 Procedure
2.4 Data Analysis
3 Results
4 Discussion
5 Conclusion
References
Motivation in Physical Activity: Smartphone Sport Tracker Applications
Abstract
1 Introduction
2 Methodology
2.1 Instrumentations
2.2 Data Collection Procedures
2.3 Statistical Analysis
3 Result
3.1 Demographics Data
3.2 The Result of Overall Satisfaction
3.3 The Result of Motivation to Do Physical Activity
3.4 The Result of Correlation Between Overall Satisfactions and Motivation Perform Physical Activity
4 Discussions
4.1 The Overall Satisfaction
4.2 The Motivation Level
4.3 Correlation Between Overall Satisfactions Using Smartphone Sport Tracker with Motivation in Physical Activity
5 Recommendations
6 Conclusion
References
The Relationship Between Motivation and Leadership Style Among PKNS Football Academy Players
Abstract
1 Introduction
1.1 Relationship Between Coach and Athlete
1.2 Leadership
1.3 Motivational Factor
1.4 Sport Performance
2 Objective
3 Methods
4 Results
4.1 Demographic Profile
4.2 Age
4.3 Preferred Leadership Style by the PKNS Football Academy
4.4 Preferred Type of Motivation by the PKNS Football Academy
4.5 Result of Relationship Between Leadership Style and Motivational Factor Among PKNS Football Academy Players
5 Discussion
6 Conclusions
References
The Effects of Brain Breaks Physical Activity Solutions on Processes of Change in Physical Activity Among the Malaysian Primary School Children
Abstract
1 Introduction
2 Methods
2.1 Study Design
2.2 Participants
2.3 Study Procedures
2.4 Brain Breaks Physical Activity Solution (BBPAS)
2.5 Processes of Change Questionnaire
2.6 Data Analysis
3 Results
4 Discussion
4.1 TTM as a Framework
4.2 BBPAS as a Physical Activity Intervention
5 Conclusion
Acknowledgement
References
The Effects of Brain-Breaks on Short-Term Memory Among Primary School Children in Malaysia
Abstract
1 Introduction
1.1 Brain Breaks Intervention
1.2 Short-Term Memory
2 Methods
2.1 Participants
2.2 Measures
2.3 Procedures
2.4 Data Analysis
3 Results
3.1 Demographic and Pilot Test
3.2 Short-Term Memory
4 Discussion
5 Conclusion
Acknowledgement
References
Effects of Using EEG Neurofeedback Device to Enhance Elite Bowlers’ Performance
Abstract
1 Introduction
2 Methods
2.1 Participants
2.2 MUSE Neuro-Feedback Training Protocol
2.3 Bowling Performance and Measure
2.4 Procedure
2.5 Data Analysis
3 Results
3.1 Normality
3.2 Baseline Similarity
3.3 CSAI-2R Scores of the Control Trial
3.4 CSAI-2R Scores Using EEG-MUSE Neurofeedback Training
3.5 Bowling Scores
4 Discussion
5 Conclusion
References
Transcranial Direct Current Stimulation Enhances Skill-Related Fitness Among the Under-15 Football Players
Abstract
1 Introduction
2 Methods
2.1 Study Design
2.2 Participants
2.3 Transcranial Direct Current Stimulation Procedures
2.4 Study Approval
2.5 Assessments
2.6 Statistical Analyses
3 Results
4 Discussion
5 Conclusion
Conflict of Interest
References
Perceived Risk and Perceived Competence in White Water Rafting Activity at Kampar River, Gopeng, Perak
Abstract
1 Introduction
2 Literature Review
2.1 Adventure Recreation
2.2 Risk
2.3 Perceived Risk and Perceived Competence
2.4 Adventure of Experience Paradigm (AEP)
2.5 Previous Studies in Perceived Risk and Perceived Competence
3 Methodology
3.1 Data Analysis
3.2 Instrumentation
3.3 Validity and Reliability
4 Results and Discussions
5 Conclusion
Acknowledgement
References
The Effects of Integrating Biofeedback Training into a 12-Week Periodized Training Program on Galvanic Skin Response and Anxiety Level Among Junior Archers
Abstract
1 Introduction
2 Materials and Methods
2.1 Subjects
2.2 Measurement and Testing Procedure
2.3 Experimental Treatment
2.4 Statistical Analysis
3 Results
4 Discussion
Acknowledgment
References
Changes in Galvanic Skin Responses Following a Single Session Training of Progressive Muscle Relaxation Technique Among Adolescent Football Players
Abstract
1 Introduction
2 Method
2.1 Participants
2.2 Measurement Procedures of Galvanic Skin Response (GSR)
2.3 Experimental Procedures
2.4 Statistical Analysis
3 Results
4 Discussion
5 Conclusion
References
Author Index
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Lecture Notes in Bioengineering
Mohd Hasnun Arif Hassan · Ahmad Munir Che Muhamed · Nur Fahriza Mohd Ali · Denise Koh Choon Lian · Kok Lian Yee · Nik Shanita Safii · Sarina Md Yusof · Nor Farah Mohamad Fauzi Editors
Enhancing Health and Sports Performance by Design Proceedings of the 2019 Movement, Health & Exercise (MoHE) and International Sports Science Conference (ISSC)
Lecture Notes in Bioengineering Advisory Editors Nigel H. Lovell, Graduate School of Biomedical Engineering, University of New South Wales, Kensington, NSW, Australia Luca Oneto, DIBRIS, Università di Genova, Genova, Italy Stefano Piotto, Department of Pharmacy, University of Salerno, Fisciano, Italy Federico Rossi, Department of Chemistry and Biology, University of Salerno, Fisciano, Italy Alexei V. Samsonovich, Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA, USA Fabio Babiloni, Department of Molecular Medicine, University of Rome Sapienza, Rome, Italy Adam Liwo, Faculty of Chemistry, University of Gdansk, Gdansk, Poland Ratko Magjarevic, Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia
Lecture Notes in Bioengineering (LNBE) publishes the latest developments in bioengineering. It covers a wide range of topics, including (but not limited to): • • • • • • • • • • •
Bio-inspired Technology & Biomimetics Biosensors Bionanomaterials Biomedical Instrumentation Biological Signal Processing Medical Robotics and Assistive Technology Computational Medicine, Computational Pharmacology and Computational Biology Personalized Medicine Data Analysis in Bioengineering Neuroengineering Bioengineering Ethics
Original research reported in proceedings and edited books are at the core of LNBE. Monographs presenting cutting-edge findings, new perspectives on classical fields or reviewing the state-of-the art in a certain subfield of bioengineering may exceptionally be considered for publication. Alternatively, they may be redirected to more specific book series. The series’ target audience includes advanced level students, researchers, and industry professionals working at the forefront of their fields. Indexed by SCOPUS and Springerlink. The books of the series are submitted for indexing to Web of Science.
More information about this series at http://www.springer.com/series/11564
Mohd Hasnun Arif Hassan Ahmad Munir Che Muhamed Nur Fahriza Mohd Ali Denise Koh Choon Lian Kok Lian Yee Nik Shanita Safii Sarina Md Yusof Nor Farah Mohamad Fauzi •
•
•
•
•
•
•
Editors
Enhancing Health and Sports Performance by Design Proceedings of the 2019 Movement, Health & Exercise (MoHE) and International Sports Science Conference (ISSC)
123
Editors Mohd Hasnun Arif Hassan Faculty of Mechanical and Automotive Engineering Technology Universiti Malaysia Pahang Pekan, Pahang, Malaysia Nur Fahriza Mohd Ali Malaysian Journal of Movement, Health & Exercise Universiti Malaysia Pahang Pekan, Pahang, Malaysia Kok Lian Yee Department of Sports Studies Universiti Putra Malaysia Selangor, Malaysia Sarina Md Yusof Faculty of Sports Science and Recreation Universiti Teknologi MARA Selangor, Malaysia
Ahmad Munir Che Muhamed Advanced Medical and Dental Institute Universiti Sains Malaysia Kepala Batas, Pulau Pinang, Malaysia Denise Koh Choon Lian Centre for Community Education & Wellbeing, Faculty of Education Universiti Kebangsaan Malaysia Selangor, Malaysia Nik Shanita Safii School of Healthcare Sciences Universiti Kebangsaan Malaysia Kuala Lumpur, Malaysia Nor Farah Mohamad Fauzi Faculty of Health Sciences Universiti Kebangsaan Malaysia Kuala Lumpur, Malaysia
ISSN 2195-271X ISSN 2195-2728 (electronic) Lecture Notes in Bioengineering ISBN 978-981-15-3269-6 ISBN 978-981-15-3270-2 (eBook) https://doi.org/10.1007/978-981-15-3270-2 © Springer Nature Singapore Pte Ltd. 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore
Preface
Two of the most prestigious annual conference relating to Sport Science and Health in Malaysia was held in Kuching, Sarawak, from September 30, 2019, to October 2, 2019. This joint conference of the 6th International Conference on Movement, Health and Exercise and the 12th International Sports Science had attracted researchers and sports practitioners from various backgrounds to share and disseminate current research updates and evidence-based findings and translate them into winning practices through scholarly communication. The theme chosen for this joint conference “Enhancing Health and Sports Performance by Design” is very relevant to the national agenda of producing world-class athletes via a systematic development program. This peer-reviewed conference proceeding highlights high-quality research findings covering 8 areas of sports science and technology, which include Exercise Sciences, Human Performance, Physical Activity and Health, Sports Medicine, Sports Nutrition, Management and Sports Studies and Sports Engineering and Technology. The publication of this proceedings in Lecture Notes in Bioengineering will assist in maximizing the accessibility of readers and the popularity of these papers. Mohd Hasnun Arif Hassan Ahmad Munir Che Muhamed Nur Fahriza Mohd Ali Denise Koh Choon Lian Kok Lian Yee Nik Shanita Safii Sarina Md Yusof Nor Farah Mohamad Fauzi
v
Organizing Committee
Chairman Ahmad Munir Che Muhamed
Lifestyle Science Cluster, Advanced Medical and Dental Institute, Universiti Sains Malaysia, Penang, Malaysia
Deputy Chairman Mohd Nidzam Jawis
School of Health Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia
Logistics Chin Ngien Siong
Department of Physical Education and Health Institute of Teacher Education, Batu Lintang Campus, Kuching, Sarawak, Malaysia
Website and Publication Mohd Hasnun Arif Hassan
Faculty of Mechanical and Automotive Engineering Technology, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia
vii
viii
Organizing Committee
Scientific Committee Noorsuzana Binti Mohd Shariff Rohayu Binti Hami
Ooi Cheong Hwa
Hazwani Binti Ahmad Yusof @ Hanafi Salbiah Bt Md Isa
Mohd Nidzam Jawis
Marilyn Ong Li Yin
Ooi Foong Kiew
Chen Chee Keong
Hairul Anuar Hashim
Oleksandr K. Krasilshchikov
Lifestyle Science Cluster, Advanced Medical and Dental Institute, Universiti Sains Malaysia, Penang, Malaysia Lifestyle Science Cluster, Advanced Medical and Dental Institute, Universiti Sains Malaysia, Penang, Malaysia Lifestyle Science Cluster, Advanced Medical and Dental Institute, Universiti Sains Malaysia, Penang, Malaysia Lifestyle Science Cluster, Advanced Medical and Dental Institute, Universiti Sains Malaysia, Penang, Malaysia Lifestyle Science Cluster, Advanced Medical and Dental Institute, Universiti Sains Malaysia, Penang, Malaysia Exercise and Sport Science Program, School of Health Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia Exercise and Sport Science Program, School of Health Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia Exercise and Sport Science Program, School of Health Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia Exercise and Sport Science Program, School of Health Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia Exercise and Sport Science Program, School of Health Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia Exercise and Sport Science Program, School of Health Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia
Contents
Exercise Science Determination of Cardiac Function Using Impedance Cardiography During Jogging With and Without Breast Support . . . . . Kunanya Masodsai and Rungchai Chaunchaiyakul
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Changes in Immune Response to Moderate Exercise in Active Trainees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Aparup Konar, Sridip Chatterjee, and Samiran Mondal
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Effects of Attentional Focus Among Novices and Elite Athletes in Sprinting Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Saidatul Nur Syuhadah Mohamed Sabadri, Jeffrey Low Fook Lee, Shaza Mohd Shah, Nursyaidatul Hafiza Madzlan, and Maisarah Mohd Saleh The Effects of Myofascial Release Using Foam Rolling and Resistance Band Assisted Stretching on Malaysian Rugby Players’ Lower Body Power and Flexibility . . . . . . . . . . . . . . . . . . . . . . Nurul Afiqah Bakar, Nurul Hidayah Amir, Ammar Md Zaini, Luke Nikol, and Mohd Hazwan Zikri Abdul Halim The Effects of High Intensity Functional Interval Training on Selected Fitness Components Among Young Badminton Players . . . Pathmanathan K. Suppiah, Angelica Joanne Joummy, Md. Safwan Samsir, Muralindran Mariappan, Hasnol Noordin, and Abdul Mu’iz Bin Nor Azmi The Effect of Amplitude (Response Complexity) in Choice Reaction Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mohd Syrinaz Azli, Mohar Kassim, Jorrye Jakiwa, Siti Azilah Atan, and Emmy Hainida Khairul Ikram
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Effect of Medial Longitudinal Arch Height on Static and Dynamic Balance Among UiTM Female Athletes . . . . . . . . . . . . . . . . . . . . . . . . . Salvastore Sam and Nur Khairunisa Abu Talip The Relative Age Effect in Malaysia Youth Athletes . . . . . . . . . . . . . . . Shaza Mohd Shah, Jeffrey Low Fook Lee, Nursyaidatul Hafiza Madzlan, Saidatul Nur Syuhadah Mohamed Sabadri, and Maisarah Mohd Saleh
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Human Performance The Acute Effects of Exercises Order During Upper-Lower Body Alternated Supersets Among Trained Men . . . . . . . . . . . . . . . . . . . . . . Muhammad Hannan Sazali, Mohamad Shahrul Azzfar, Nur Ikhwan Mohamad, and Ali Md. Nadzalan Body Composition and Muscular Performance of Malaysian Young Male State Level Weightlifting, Cycling and Squash Athletes . . . Norsuriani Samsudin, Foong Kiew Ooi, and Chee Keong Chen
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Development of a Soccer-Specific Running Protocol for Young Soccer Players . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 Siti Azilah Atan and Mohar Kassim The Potentiating Effects of an Eccentric Load on Horizontal Jumps Among Handball Players . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 M. N. Muhammad Zulqarnain, A. Jasmi, T. Wahidah, S. M. P. Sharifah Maimunah, and Adam Linoby The Confirmatory Factor Analysis of the Malay Language Revised Competitive State Anxiety Inventory-2 (CSAI-2R) Among Adolescent Malaysian State Level Athletes . . . . . . . . . . . . . . . . 123 Liew Guo Chen, Hairul Anuar Hashim, Ngien Siong Chin, Yee Cheng Kueh, and Garry Kuan Conventional Jump Warm-Up with and Without Jumping Rope on Jumping Ability Among Volleyball Players . . . . . . . . . . . . . . . . . . . . 134 Lawrence Balang Bungkong, Nur Khairunisa Abu Talip, and Wan Firdaus Wan Chik Identification of Running, Jogging and Walking Activities for Female Athletes Indoor Hockey in 2016 PON Matches . . . . . . . . . . 142 Mohammad Faruk, Irmantara Subagio, and Heryanto Nur Muhammad Carbohydrate Mouth Rinsing in Thermoneutral Enhances Prolonged Running Performance Compared to Hot-Humid Environment . . . . . . . 148 Harris Kamal Kamaruddin, Cheong Hwa Ooi, and Ahmad Munir Che Muhamed
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Which Joint Angle Changes Have Most Influence on Dart Release Speed? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 Nurhidayah Omar, Farah Syahida Abdul Nasir, and Ahmad Faizal Salleh The Influence of Anthropometrics, Physical Fitness, and Technical Skill on Performance of U-12 Youth Soccer Players in Malaysia . . . . . . 170 Ahmad Bisyri Husin Musawi Maliki, Mohamad Razali Abdullah, Mohamad Shafaat Fadzil, Muhd Faris Nazer, Muhammad Hafiz Zufaimey Ismail, Khairie Koh Abd Hadi Koh, Noraini Nazarudin, Siti Musliha Mat-Rasid, Mohd Syaiful Nizam Abu Hassan, Amr Alnaimat, Muhammad Rabani Hashim, Hafizan Juahir, and Rabiu Muazu Musa Management and Sports Studies Identifying Element of Academic Enhancement Support for Student-Athlete Using Fuzzy Delphi Method . . . . . . . . . . . . . . . . . . 183 Mohd Zulfadli Rozali, Saifullizam Puteh, Faizal Amin Nur Yunus, Affero Ismail, and Thariq Khan Azizuddin Khan A Review of Pathways Towards Expert Performance on Elite Youth Athletes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189 Mohd Faridz Ahmad, Jeffrey Low Fook Lee, and Ali Md Nadzalan The Relationship Between Organizational Commitment and Internal Service Quality Among the Staff in Majlis Sukan Negeri-negeri in Malaysia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 Phylicia Phoa Siew Ching, Mohamad Nizam Nazarudin, and Pathmanathan K. Suppiah Accessibility Dimensions (Factors) of Parks and Playgrounds . . . . . . . . 206 Ellail Ain Mohd Aznan, Ahmad Fikri Mohd Kassim, Nurul Hidayah Amir, Mohd Khairulanwar Md Yusof, Mohd Syafiq Miswan, and Nur Anis Fatima Amir Physical Activity and Health Influence of Individual Physical Activity on EMG Muscle Activation Pattern . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215 Maisarah Sulaiman, Aizreena Azaman, and Azli Yahya Immediate Effect of Single Bout of Karate Exercise on Heart Rate . . . . 223 Puneet Bhattacharya and Sridip Chatterjee Incorporating Traditional Games in Physical Education Lesson to Increase Physical Activity Among Secondary School Students: A Preliminary Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235 ‘Arif Azlan, Nadzirah Ismail, Nor Farah Mohamad Fauzi, and Ruzita Abd Talib
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Muscle Strength Time Activity . . Norsham Juliana, Nur Islami Mohd
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in Male Youth that Play Archery During Leisure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 248
Izuddin Fahmy Abu, Nadia Ahmad Roslan, Fahmi Teng, Abd Rahman Hayati, and Sahar Azmani
The Effect of Zone, Gender, RAE and Fitness Variables Towards Fitness Status and Anthropometric Attributes of Children in Malaysia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 257 Ahmad Bisyri Husin Musawi Maliki, Mohamad Razali Abdullah, Siti Musliha Mat-Rasid, Hafizan Juahir, Mohd Syaiful Nizam Abu Hassan, Nik Naleesa Nasuha Rusmadi, Muhammad Ziyad Yazid, Fatin Zulaikha Azmin, Tengku Nur Arnie Tengku Ghazali, Amr Salem Falah, Muhammad Rabani Hashim, and Rabiu Muazu Musa Sports Engineering and Technology Offline LabVIEW-Based EEG Signals Analysis to Detect Vehicle Driver Microsleep . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271 N. Sulaiman, K. S. Goh, M. Rashid, S. Jadin, M. Mustafa, M. Z. Ibrahim, and F. Samsuri Vision Based Automated Badminton Action Recognition Using the New Local Convolutional Neural Network Extractor . . . . . . . . . . . . 290 Nur Azmina Rahmad, Muhammad Amir As’ari, Mohamad Fauzi Ibrahim, Nur Anis Jasmin Sufri, and Keerthana Rangasamy Investigation of Different Time-Series Segmented Windows from Inertial Sensor for Field Hockey Activity Recognition . . . . . . . . . . 299 Norazman Shahar, Nurul Fathiah Ghazali, Muhammad Amir As’ari, Tian Swee Tan, and Mohamad Fauzi Ibrahim Effect of Stroke Rate Increment on Power Output and Foot Asymmetries Force Among Malaysian University Rower . . . . . . . . . . . . 311 Fakhrizal Azmy Nasruddin, Ab Aziz Mohd Yusuf, Mohd Azizi Abdul Rahman, Muhammad Ridwan Jaafar, Hadafi Fitri Mohd Latip, and Muhamad Noor Harun Object Detection Approach Using Single Shot Multibox Detector for Sprinting Movement Recognition . . . . . . . . . . . . . . . . . . . . . . . . . . . 318 Muhamad Khairi Kamarudin, Muhammad Haikal Satria, Hadafi Fitri Mohd Latip, and Atikah Muhammad Physical Fatigue Prediction Based on Heart Rate Variability (HRV) Features in Time and Frequency Domains Using Artificial Neural Networks Model During Exercise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 326 Zulkifli Ahmad, Mohd Najeb Jamaludin, and Ummu Kulthum Jamaludin
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The Effect of Compression Socks on Running Kinematics in Experience and Novice Runners . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333 Muhammad Hanis Jefry, Hosni Hasan, Mohd Azim Nural Azhan, Mohd Iqbal Misnon, Raja Mohamed Firhad Raja Azidin, and Hashbullah Ismail The Classification of Skateboarding Trick Manoeuvres: A K-Nearest Neighbour Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341 Muhammad Ar Rahim Ibrahim, Muhammad Amirul Abdullah, Muhammad Nur Aiman Shapiee, Mohd Azraai Mohd Razman, Rabiu Muazu Musa, Muhammad Aizzat Zakaria, Noor Azuan Abu Osman, and Anwar P. P. Abdul Majeed The Application of Artificial Neural Networks in Predicting Blood Pressure Levels of Youth Archers by Means of Anthropometric Indexes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 348 Rabiu Muazu Musa, Muhammad Zuhaili Suhaimi, Anwar P. P. Abdul Majeed, Mohamad Razali Abdullah, Siti Musliha Mat-Rasid, and Mohd Hasnun Arif Hassan Sports Medicine Prevalence of Cardiovascular Risk Factors Among Professional Football Athletes in Sabah, Malaysia . . . . . . . . . . . . . . . . . . . . . . . . . . . 361 Mohamad Azwan Aziz, Muhammad Yusri Yunus, and Redzal Abu Hanifah External Snapping Hip Syndrome: A Case Report of a Professional Hockey Player . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 372 Muhammad Yusri Yunus, M. G. Matthew, and Redzal Abu Hanifah Ouch! My Hip Hurts: A Rare Case Report of Rectus Femoris Muscle Tear Causing Failure in Hip Extension . . . . . . . . . . . . . . . . . . . 379 Lavinen Kumar Sugumar, G. M. Mariam, and M. Y. Yau Sports Nutrition A Randomized Controlled Trial of the Effects of Dietary Nitrate Supplementation on Blood Pressure, Exhaled Nitric Oxide Level and Maximal Isometric Handgrip Strength in Pre-hypertensive Women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389 Adam Linoby, Ameerul Adzim Azrin, Mohd Aizzat Adnan, Nur Hidayah Asilah Za’don, Mohd Hanifa Sariman, Muhammad Zulqarnain Mohd Nasir, and Raja Nurul Jannat Raja Hussain The Effect of Various Carbohydrate Concentrations Mouth Rinsing on Intermittent Running Performance . . . . . . . . . . . . . . . . . . . . . . . . . . 399 Nur Athirah Idrus, Al Hafiz Abu Bakar, Mohd Faiz Putra Abd Razak, Norfaezah Mohd Rosli, Ahmad Fikri Mohd Kassim, and Harris Kamal Kamaruddin
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Nitrate-Rich Red Spinach Extract Supplementation Increases Exhaled Nitric Oxide Levels and Enhances High-Intensity Exercise Tolerance in Humans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 412 Adam Linoby, Mohd Nurthaqif, Muhamad Noor Mohamed, Maisarah Mohd Saleh, Yusandra Md Yusoff, Noor Azila Azreen Md Radzi, Siti Aishah Abd Rahman, and Saidatul Nur Syuhadah Mohamed Sabadri The Role of Fitness Status in the Performance-Enhancing Effects of Dietary Inorganic Nitrate Supplementation: Meta-analysis and Meta-regression Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 421 Adam Linoby, Sarina Md Yusof, Ahmad Dzulkarnain Ismail, Kalam Azad Isa, Syed Shahbudin Syed Omar, Masshera Jamaludin, and Sharifah Maimunah Syed Mud Puad An Overview of a Dietary Pattern Among Malaysian Endurance Athletes in Relation to Glycemic Index . . . . . . . . . . . . . . . . . . . . . . . . . 435 Zaini Bahari, Nik Shanita Safii, and Ahmad Munir Che Muhamed Sports Psychology Coach-Athlete Relationship and Coaching Effectiveness in Team Sports Athletes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 451 Ahmad Fikri Mohd Kassim, Wan Faizal Iskandar Wan Abdullah, Siti Jameelah Md Japilus, and Asmahan Shahirah Azanuar Yusri Motivation in Physical Activity: Smartphone Sport Tracker Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 463 Siti Fadhilah Abdul Hamid, Nur Nadiah Ismail, Fatin Aqilah Abdul Razak, and Nurul Nadiah Shahudin The Relationship Between Motivation and Leadership Style Among PKNS Football Academy Players . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 471 Syed Husin Syed Ahmad and Vincent Parnabas The Effects of Brain Breaks Physical Activity Solutions on Processes of Change in Physical Activity Among the Malaysian Primary School Children . . . . . . . . . . . . . . . . . . . . . . . . . 481 Hussein Rizal, Mawar Siti Hajar, Ayu Suzailiana Muhamad, and Garry Kuan The Effects of Brain-Breaks on Short-Term Memory Among Primary School Children in Malaysia . . . . . . . . . . . . . . . . . . . . . . . . . . 493 Mawar Siti Hajar, Hussein Rizal, Ayu Suzailiana Muhamad, and Garry Kuan Effects of Using EEG Neurofeedback Device to Enhance Elite Bowlers’ Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 503 Qasim Raza, Marilyn Li Yin Ong, and Garry Kuan
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Transcranial Direct Current Stimulation Enhances Skill-Related Fitness Among the Under-15 Football Players . . . . . . . . . . . . . . . . . . . . 511 Mohammad Saifatullizam Mustafa, Marilyn Li Yin Ong, Siti-Azrin Ab Hamid, and Garry Kuan Perceived Risk and Perceived Competence in White Water Rafting Activity at Kampar River, Gopeng, Perak . . . . . . . . . . . . . . . . . . . . . . . 519 Hajar Asmidar Samat, Nelfianty Mohd Rasyid, Thariq Khan Azizuddin Khan, Mohd Noorazlan Ab Aziz, Mustakim Hashim, and Helme Basal The Effects of Integrating Biofeedback Training into a 12-Week Periodized Training Program on Galvanic Skin Response and Anxiety Level Among Junior Archers . . . . . . . . . . . . . . . . . . . . . . . 528 Mon Redee Sut Txi, Hairul Anuar Hashim, and Oleksandr Krasilshchikov Changes in Galvanic Skin Responses Following a Single Session Training of Progressive Muscle Relaxation Technique Among Adolescent Football Players . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 538 Sharifah Maimunah Syed Mud Puad and Hairul Anuar Hashim Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 547
Exercise Science
Determination of Cardiac Function Using Impedance Cardiography During Jogging With and Without Breast Support Kunanya Masodsai1,2(&) and Rungchai Chaunchaiyakul1 1
College of Sports Science and Technology, Mahidol University, Nakhon Pathom 73170, Thailand [email protected] 2 Faculty of Sports Science, Chulalongkorn University, Bangkok 10330, Thailand
Abstract. The goal of this study was to use a non-invasive method of impedance cardiography to investigate the consistency of cardiac variables, in parallel with metabolic function. Thirteen healthy females underwent two randomized jogging conditions: without breast support (NB) and with breast support (jogging bra, JB). Cardiorespiratory and metabolic functions were continuously recorded at rest, during exercise on the treadmill at a constant speed of 4 mph at 60, 70 and 80% of age-predicted maximum heart rate followed by a 5-min recovery. The results showed that there were no significant differences in resting cardiac variables, including cardiac output (CO), heart rate (HR), stroke volume (SV), end diastolic volume (EDV), end systolic volume (ESV) and cardiac index (CI). The parallel intensity-dependent characteristics of both cardiorespiratory and metabolic variables during jogging were also determined. The results showed normal cardiac functions during and after jogging with no significant differences of CO, HR, SV, EDV, ESV and CI between two conditions (P > 0.05). Metabolic variables showed no significant differences _ 2 ), carbon between the two conditions (P > 0.05) for oxygen consumption (VO _ dioxide production (VCO ) and respiratory exchange ratio (RER). With narrow 2 ranges of the standard errors of the mean and parallel alterations of metabolism at rest, during exercise and recovery from two conditions, this study concluded that a non-invasive impedance cardiography method can possibly reflect changes of both cardiorespiratory and metabolic functions. In addition, it is suggested that breast supports in females during treadmill running induce no limitations on both cardiorespiratory and metabolic functions. Keywords: Running bra impedance Metabolism
Breast support Gas exchange Cardiac
1 Introduction Hemodynamic determination is usually conducted via invasive hemodynamic measurement such as the Swan-Ganz catheter, with unsure results [1]. Invasive Swan-Ganz catheter method can only be done at rest and not during physical activity [2]. Another © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 3–12, 2020. https://doi.org/10.1007/978-981-15-3270-2_1
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K. Masodsai and R. Chaunchaiyakul
non-invasive method, echocardiography, can be done only at pre- and immediate postexercise [3]. Clinical and exercise specialists have looked at alternative methods to measure cardiac functions during physical activity under certain stresses such as during physical activity. Impedance cardiography (ICG), a non-invasive method for the estimation of hemodynamic variables, is based on the assumption that the thorax is a homogeneous fluid cylinder, composed of blood, tissues, air and organs. Therefore, these tissues contain a fixed resistance. So, to measure ICG a low steady current amplitude (1.5 mA, 86 kHz) generated by external electrodes (located in the thoracic and cervical skin regions) can be captured as instantaneous voltage changes around the thoracic cavity according to Ohm’s law [4]. When a steady minimal electric current is applied to the thorax, the voltage changes are directly proportional to the impedance changes. Baseline thoracic impedance (Z0) is the sum of the impedance of all constant thoracic components. The alteration of dynamic Z (dZ/dt) is, therefore, derived solely from fluid changes, and then converted to stroke volume and cardiac output values using mathematical algorithms [5]. Validations of non-invasive cardiac impedance has been shown during constant cycling exercise in healthy fit subjects [6], in patients with lung problems [7] and in children [8]. It has been reported that this method could also give relevant cardiac information during non-steady motion such as running. Active females have been shown to be at high risk of breast pain from repeated excessive breast swinging motions [9]. However, only 13% of adolescent females [10] and 41% of women use jogging bra during physical activity [11] because they report discomfort from tightness, mastalgia and dyspnea [11, 12] and the belief that a jogging bra will diminish lung functions and deviated respiratory pattern toward rapid and shallow breathing [13]. It has been reported that the numbers of females involved with physical activity has been increasing [14]. Few studies have focused on in-depth cardiac variables in females jogging without breast support [15, 16]. The purpose of this study was to use this non-invasive ICG method to investigate the characteristics of changes in cardiorespiratory system during different metabolic demands in female subjects during treadmill running by comparing cardiorespiratory and metabolic functions with and without breast support.
2 Materials and Methods 2.1
Participants
Thirteen healthy active females (ages 20–25 yrs), with B and C breast cup sizes, voluntarily participated in this study. Inclusion criteria consisted of those who were free from cardiorespiratory and musculoskeletal disorders, had regular menstrual cycle within 6 months prior to participating in the study, not using hormone replacement therapy, non-pregnant, non-smoking and non-alcoholism. Objectives, experimental procedures, risks and benefits of the study were explained to potential study
Determination of Cardiac Function Using Impedance Cardiography
5
participants before completing the informed consent forms. Individual bra size was identified [10], then an appropriate jogging bra was provided for each individual. Subjects’ instructions were provided to remind them to keep their normal diets and consume enough water to ensure euhydration status. Each subject was informed to avoid coffee, tea, tobacco or alcohol, and strenuous physical activity on the day prior to testing. This study was conducted under the Human Research Ethics Committee of Mahidol University, Thailand (MU-IRB 2013/159.1112). 2.2
Experimental Procedures
For confidential, only female investigators were allowed to conduct the tests in the closed room within the laboratory. Prior to exercise testing, each subject’s anthropometric data was collected as well as estimated physical activity level using a questionnaire. The treadmill running tests were conducted on two separate occasions. Each visit was randomized with subjects either not wearing a bra (NB) or wearing a jogging bra (JB). The tests were performed at the same phase of their menstrual cycle. Prior to the treadmill test each subject performed a callisthenic warm up, then the treadmill exercise was started at 2 mph, for 3 min. A constant speed of 4 mph was continuously kept up to 80% of age-predicted maximum heart rate (MHR). Various parameters were collected at rest, 60%, 70%, and 80% of MHR, and 5 min of recovery. Gas analyzer (Oxycon Mobile, German) had been utilized to determine respiratory functions, including respiratory rate (RR), tidal volume (VT), minute ventilation (VE) and _ 2 ), carbon dioxide production metabolic functions, including oxygen consumption (VO _ (VCO 2 ) and respiratory exchange ratio (RER). Cardiac functions, including cardiac output (CO), heart rate (HR), stroke volume (SV), end diastolic volume (EDV), end systolic volume (ESV), cardiac index (CI), were continuously monitored by using noninvasive impedance cardiography method (Physioflow®, France). 2.3
Statistical Analysis
All data were presented as mean ± standard error of mean (SEM). Two-ways ANOVA-repeated measure was used for significant difference analysis with Tukey’s post hoc test. Significant level was accepted at P-value less than 0.05.
3 Results 3.1
General Characteristics
Subjects age and height were 22.85 ± 2.69 years and 163.1 ± 1.42 cm respectively. General characteristics (Table 1) revealed the normal ranges of their anthropometric variables within this age [17]. No significant differences of the above variables within three months of this crossover design experiment.
6
K. Masodsai and R. Chaunchaiyakul Table 1. Baseline characteristics of female subjects during the study. Variables Weight (kg) BMI (kg.m−2) Body fat (%) Lean body mass (%) Waist circumference (cm) Hip circumference (cm) BMI, body mass index.
3.2
No bra (n = 13) 56.45 + 5.79 21.70 + 1.77 22.91 + 2.75 28.03 + 1.67 74.38 + 6.40 94.88 + 5.02
Jogging 56.29 + 21.78 + 22.93 + 28.15 + 74.66 + 94.34 +
bra (n = 13) 5.60 1.68 2.70 1.69 6.83 5.19
Resting Cardiac Variables
Most of the resting cardiac variables in the present study (Table 2) were in the ranges of other references. While HR, EDV and ESV fell in the ranges covered by other methods, CO, and CI showed slightly lower values. Even though different methods were used from other studies, it was quite confident to conclude that impedance cardiography reflected the reliable resting cardiac variables. Table 2. Resting cardiac variables including HR, SV, CO, CI, EDV and ESV measured from _ 2 max. Methods of determinations and references the present study with additional value of VO are defined. Variables Heart rate (bpm) Stroke volume (ml/beat) Cardiac output (L/min) Cardiac index (L/min/m2) End diastolic volume (ml) End systolic volume (ml) _ 2 max (ml/min/kg) VO
This study 72.39 ± 2.38 51.36 ± 3.25 3.76 ± 0.25 2.38 ± 0.15 111.19 ± 5.57 59.83 ± 3.95 36.82 ± 1.14
Ranges/Methods/References 68.9 ± 0.8/myocardial perfusion imaging/ [18] 49-112/echo magnetic resonance imaging/ [19] 5-7/Dye dilution/ [20] 3-5/Dye dilution/ [20] 76-161/echo magnetic resonance imaging/ [19] 17-63/echo magnetic resonance imaging/ [19] 22.6 ± 4.3, Quantitative Radionucleotide Angiography/ [21] 34.0-41.8/in-direct methods/ [17]
_ 2 max, maximal oxygen consumption. VO
3.3
Changes in Metabolic Variables During Exercise
_ 2 and VCO _ During jogging, changes in VO 2 (Fig. 1A and B) significantly increased _ _ 2 and VCO from resting values in both conditions. In NB, VO 2 values declined _ immediately as jogging was ceased. But VO2 in JB recovered after the first minute _ (P < 0.05) while VCO 2 recovered after 3 min (P < 0.05). Increasing in RER of both conditions was shown after 70%MHR intensity throughout the study period (P < 0.05). No significant differences between conditions were found.
Determination of Cardiac Function Using Impedance Cardiography
3.4
7
Changes in Cardiac Variables During Exercise
Most of cardiac variables showed the intensity-dependent characteristics (Fig. 2) with narrow SEM ranges for both conditions. During jogging, there were increasing of EDV, SV, HR, CO and CI (Fig. 2A, C, D, E and F). During recovery, there were increasing of HR, CO and CI (Fig. 2D, E and F). ESV showed steady values throughout the study (Fig. 2B). No significant differences between conditions were found.
_ 2 , VCO _ Fig. 1. Changes in metabolic variables, VO 2 and RER during and after jogging. Symbols a and b represent significant different from resting values of NB and JB respectively.
3.5
Changes in Respiratory Variables During Exercise
Most of respiratory variables increased as intensity-dependent characteristics where RR, VT and VE significantly increased from resting values during jogging but immediately recover as exercise was ceased (Fig. 3A, B and C). No significant differences between conditions were found.
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K. Masodsai and R. Chaunchaiyakul
Fig. 2. Changes of cardiac variables at rest, during jogging and recovery. Symbols a and b represent significant different from resting values of NB and JB respectively.
4 Discussion There are parallel alterations of metabolism at rest, during exercise, and recovery from two jogging conditions of without and with breast support. In addition, with narrow ranges of the standard errors of the mean from both metabolic and cardiorespiratory variables, this non-invasive impedance cardiography method reflects changes of both cardiorespiratory functions. It is suggested that breast supports in females during physical activity induce no limitations on both cardiorespiratory and metabolic functions. With post-jogging discomfort, jogging without breast support is not recommended. The durations when subjects in NB condition approached 60, 70 and 80%MHR were 7.06 + 1.66, 12.08 + 2.82 and 14.88 + 1.95 min, whereas in JB were 8.50 + 1.80, 14.82 + 2.80 and 23.05 + 3.23 min (means + SEM) respectively. There was significant different jogging duration between NB and JB only at 80% MHR (P < 0.05). In addition, subjects in NB complained breast discomfort by the end of jogging. The steeper heart rate responses at 80%MHR of NB condition from this study imply that jogging exercise without breast support is not recommended [16, 22].
Determination of Cardiac Function Using Impedance Cardiography
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This study shows the coexistent changes of cardiorespiratory and metabolism _ 2 , of either NB or JB reveal no limitation of metabolism functions. No changes in VO generated from sports bra during exercise. Metabolism during exercise shows an intensity-dependent pattern for both NB and JB. However, JB induced higher meta_ 2 and bolic demand during first few minutes of recovery. It was determined that VO _ VCO 2 at rest was approximately about 250 and 200 ml/min respectively [23]. This _ _ causes the ratio between VCO 2 /VO2 (RER) to be 0.8. During higher metabolic _ _ 2 and VCO demand, like exercise, increasing in VO 2 is known to be intensitydependent [24]. This will cause deviations of RER from 0.8 towards nearly or above 1.00 which reflects carbohydrate aerobic combustion. If exercise intensity is prolonged, RER may deviate toward 0.7 for fat metabolism [23–26]. The deviations of RER remain even though exercise had been stopped. This reflects that the existing and continuing of high metabolism. Higher RER > 1.00 during recovery in jogging bra condition likely indicates the involvement of anaerobic processes [27]. Thus, 5 min recovery period in the present study was not appropriate for exercise at moderate to high intensity of >80% MHR.
Fig. 3. Changes of respiratory variables at rest, during jogging and recovery. Symbols a and b represent significant different from resting values of NB and JB respectively.
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The feeling of chest wall restriction will change breathing pattern from unsatisfied sensation [13]. If this really exists, we might find differences in resting respiratory variables in JB but not in NB. With no significant different between resting respiratory variables between NB and JB (Fig. 3), we conclude that putting on jogging bra will not induce any changes in breathing pattern as previously believed. At very high pressure models, this will cause skin furrows [27], and alters respiratory pattern [28, 29]. An immediate ventilator responses to exercise is proposedly derived from neural drives and later from blood-borne mediators from exercising muscles [30]. During low to moderate exercise, increasing in VT and RR are in the proportion to intensity [31]. Increasing too fast breathing frequency will induce higher airways resistance even in normal healthy subjects [32]. The present study found effective respiratory adjustments during recovery. Physical activity induces higher ventricular contraction. Thus, cardiac contractility and rhythm are activated [33]. Increasing of HR and SV resulted in higher cardiac output [34]. These compensatory conditions remain similarly with NB and chest wall strapping (JB). In contrast to a previous study, lung volumes were diminished to 35% from extremely high chest wall restriction [34]. In our model, low elastic recoil of elastic bra’s garment may not affect hemodynamic within the thorax. Increasing in SV and CO in both NB and JB during jogging is most likely associated with higher RR [35], which possibly affect cardiac function and will bring about higher SV [34]. With constant body surface area, increasing in CI is mainly due to increasing in CO. This means that suitable hemodynamic to all body parts is maintained [36]. In parallel to metabolic variables, it was shown that cardiac variables in sedentary females (ages 23– 26 yrs) during treadmill exercise increased in parallel to metabolic variables [37]. These characteristics were found in moderately trained females (18–30 yrs) [38].
5 Conclusion The parallel concomitant changes of metabolism and cardiorespiratory systems under the same stress reveal that non-invasive impedance cardiography method can be used to determine changes in cardiorespiratory system. This study also indicates no limitation of jogging bra on metabolic and cardiovascular profiles during constant speed jogging. In addition, jogging bra is recommended for safety and effectively for breast support without functional limitation.
References 1. Robin, E.D.: The cult of the Swan-Ganz catheter. Overuse and abuse of pulmonary flow catheters. Ann. Intern. Med. 103(3), 445–449 (1985) 2. Fields, C., Trotsky, A., Fernandez, N., Smith, B.A.: Mobility and ambulation for patients with pulmonary artery catheters: a retrospective descriptive study. J. Acute Care Phys. Ther. 6(2), 64–70 (2015) 3. Grazioli, G., Sanz, M., Montserrat, S., Vidal, B., Sitges, M.: Echocardiography in the evaluation of athletes. F1000Res. 4, 151 (2015)
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4. Silva, L.D.S., Reis, F.F., Silva, M.E.S., Lima, D.V.M.D.: Accuracy of impedance cardiography in acute myocardial infarction: a literature review. Int. J. Cardiovasc. Sci. 31 (3), 282–289 (2018) 5. Mehta, Y., Arora, D.: Newer methods of cardiac output monitoring. World J. Cardiol. 6(9), 1022–1029 (2014) 6. Tordi, N., Mourot, L., Matusheski, B., Hughson, R.L.: Measurements of cardiac output during constant exercises: comparison of two non-invasive techniques. Int. J. Sports Med. 25 (2), 145–149 (2004) 7. Bougault, V., Lonsdorfer-Wolf, E., Charloux, A., Richard, R., Geny, B., OswaldMammosser, M.: Does thoracic bioimpedance accurately determine cardiac output in COPD patients during maximal or intermittent exercise? Chest 127(4), 1122–1131 (2005) 8. Welsman, J., Bywater, K., Farr, C., Welford, D., Armstrong, N.: Reliability of peak VO(2) and maximal cardiac output assessed using thoracic bioimpedance in children. Eur. J. Appl. Physiol. 94(3), 228–234 (2005) 9. Brown, N., White, J., Brasher, A., Scurr, J.: The experience of breast pain (mastalgia) in female runners of the 2012 London Marathon and its effect on exercise behaviour. Br. J. Sports Med. 48(4), 320–325 (2014) 10. McGhee, D.E., Steele, J.R.: Optimising breast support in female patients through correct bra fit. A cross-sectional study. J. Sci. Med. Sport. 13(6), 568–572 (2010) 11. Bowles, K.A., Steele, J.R., Munro, B.: What are the breast support choices of Australian women during physical activity? Br. J. Sports Med. 42(8), 670–673 (2008) 12. Bowles, K.A., Steele, J.R., Chaunchaiyakul, R.: Do current sports brassiere designs impede respiratory function? Med. Sci. Sports Exerc. 37(9), 1633–1640 (2005) 13. O’Donnell, D.E., Hong, H.H., Webb, K.A.: Respiratory sensation during chest wall restriction and dead space loading in exercising men. J. Appl. Physiol. 88(5), 1859–1869 (2000) 14. Sherar, L.B., Gyurcsik, N.C., Humbert, M.L., Dyck, R.F., Fowler-Kerry, S., Baxter-Jones, A.D.: Activity and barriers in girls (8–16 yr) based on grade and maturity status. Med. Sci. Sports Exerc. 41(1), 87–95 (2009) 15. Mills, C., Risius, D., Scurr, J.: Breast motion asymmetry during running. J. Sports Sci. 33(7), 746–753 (2015) 16. Scurr, J.C., White, J.L., Hedger, W.: The effect of breast support on the kinematics of the breast during the running gait cycle. J. Sports Sci. 28(10), 1103–1109 (2010) 17. Sport Authority of Thailand: Physical fitness norms of Thai population. Sports Science Sector, Sports Science Department, Sport Authority of Thailand, Bangkok 2002 18. Yamada, A.T., Campos Neto Gde, C., Soares Jr, J., Giorgi M.C., Araujo F., Meneghetti J.C., et al.: Gender differences in ventricular volumes and left ventricle ejection fraction estimated by myocardial perfusion imaging: comparison of Quantitative Gated SPECT (QGS) and Segami software programs. Arq. Bras. Cardiol. 88(3), 285–290 (2007) 19. Cain, P.A., Ahl, R., Hedstrom, E., Ugander, M., Allansdotter-Johnsson, A., Friberg, P., et al.: Age and gender specific normal values of left ventricular mass, volume and function for gradient echo magnetic resonance imaging: a cross sectional study. BMC Med. Imag. 9, 2 (2009) 20. Katori, R.: Normal cardiac output in relation to age and body size. Tohoku J. Exp. Med. 128 (4), 377–387 (1979) 21. Higginbotham, M.B., Morris, K.G., Coleman, R.E., Cobb, F.R.: Sex-related differences in the normal cardiac response to upright exercise. Circulation 70(3), 357–366 (1984) 22. Haake, S., Scurr, J.: A dynamic model of the breast during exercise. Sports Eng. 12(4), 189– 197 (2010)
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23. Sedlock, D.A., Lee, M.G., Flynn, M.G., Park, K.S., Kamimori, G.H.: Excess postexercise oxygen consumption after aerobic exercise training. Int. J. Sport Nutr. Exerc. Metab. 20(4), 336–349 (2010) 24. Gore, C.J., Withers, R.T.: Effect of exercise intensity and duration on postexercise metabolism. J. Appl. Physiol. 68(6), 2362–2368 (1990) 25. Hagberg, J.M., Mullin, J.P., Nagle, F.J.: Effect of work intensity and duration on recovery O2. J. Appl. Physiol. Respir. Environ. Exerc. Physiol. 48(3), 540–544 (1980) 26. Sperlich, B., Born, D.P., Kaskinoro, K., Kalliokoski, K.K., Laaksonen, M.S.: Squeezing the muscle: compression clothing and muscle metabolism during recovery from high intensity exercise. PLoS ONE One 8(4), e60923 (2013) 27. Guenette, J.A., Witt, J.D., McKenzie, D.C., Road, J.D., Sheel, A.W.: Respiratory mechanics during exercise in endurance-trained men and women. J. Physiol. 581(Pt 3), 1309–1322 (2007) 28. Casaburi, R., Storer, T.W., Wasserman, K.: Mediation of reduced ventilatory response to exercise after endurance training. J. Appl. Physiol. 63(4), 1533–1538 (1987) 29. Coast, J.R., Cline, C.C.: The effect of chest wall restriction on exercise capacity. Respirology 9(2), 197–203 (2004) 30. Casaburi, R.: The mechanism of the exercise hyperpnea: the ultrasecret revisited. Am. J. Respir. Crit. Care Med. 186(7), 578–579 (2012) 31. Carey, D., Pliego, G., Raymond, R.L.: How endurance athletes breathe during incremental exercise to fatigue: interaction of tidal volume and frequency. J. Exerc. Physiol. 11(4), 44–51 (2008) 32. Chaunchaiyakul, R., Groeller, H., Clarke, J.R., Taylor, N.A.: The impact of aging and habitual physical activity on static respiratory work at rest and during exercise. Am. J. Physiol. Lung Cell. Mol. Physiol. 287(6), L1098–L1106 (2004) 33. Dyakova, E.Y., Kapilevich, L.V., Shylko, V.G., Popov, S.V., Anfinogenova, Y.: Physical exercise associated with NO production: signaling pathways and significance in health and disease. Front. Cell Dev. Biol. 3, 19 (2015) 34. Miller, J.D., Beck, K.C., Joyner, M.J., Brice, A.G., Johnson, B.D.: Cardiorespiratory effects of inelastic chest wall restriction. J. Appl. Physiol. 92(6), 2419–2428 (2002) 35. Mendonca, C.T., Schaeffer, M.R., Riley, P., Jensen, D.: Physiological mechanisms of dyspnea during exercise with external thoracic restriction: role of increased neural respiratory drive. J. Appl. Physiol. 116(5), 570–581 (2014) 36. Klabunde, R.E.: Cardiovascular Physiology Concepts, 2nd edn. Lippincott Williams & Wilkins, Philadelphia (2012) 37. Ogawa, T., Spina, R.J., Martin 3rd, W.H., Kohrt, W.M., Schechtman, K.B., Holloszy, J.O., et al.: Effects of aging, sex, and physical training on cardiovascular responses to exercise. Circulation 86(2), 494–503 (1992) 38. Ferguson, S., Gledhill, N., Jamnik, V.K., Wiebe, C., Payne, N.: Cardiac performance in endurance-trained and moderately active young women. Med. Sci. Sports Exerc. 33(7), 1114–1119 (2001)
Changes in Immune Response to Moderate Exercise in Active Trainees Aparup Konar1(&), Sridip Chatterjee2, and Samiran Mondal3 1
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Office of the Director of Physical Instruction, Sports Board, Jadavpur University, Kolkata 700032, West Bengal, India [email protected] 2 Department of Physical Education, Jadavpur University, Kolkata 700032, West Bengal, India Department of Physical Education, Visva Bharati University, Santiniketan 731235, West Bengal, India
Abstract. Many questions are still reaming about the mechanism by which regular moderate training to the magnitude of the specific immune response. The purpose of this study was to investigate the influence of regular moderate training on specific immune response in human body. A less air polluted zone of Burdwan, West Bengal, India was selected for this study. Total 32 male subjects chosen out of which 18 subjects (mean age 25 ± 2.06 years) treated as regular habit of Moderately Trained (MT) group and 14 subjects (mean age 22.5 ± 1.79 years) were act as Sedentary Control (SC) group from the same area. Specific immune variables such as Immunoglobulin G (IgG), CD4 (Helper T cells) percentage, CD4/CD8 ratio, Albumin and Albumin Globulin ratio were examined. Mean, SD and independent ‘t’ test were used for statistical analysis by using IBM SPSS 20.0 version software. The higher mean were observed in MT group compared to SC group in all specific immune variables although there was no significant difference found between both groups. Regular moderate training habit may be increased in modulating the specific Immune response which is a possible biologic efficiency to foster the defense against disease on human health. Keywords: Moderate training students
Immune response & physical education
1 Introduction The immune system is the vital body system that improves one’s sense of wellbeing & general health and does a remarkable job of defending against disease causing microorganism. Exercise and training habit may be the most effective defense mechanism to produce strong functioning of immune system on human health. Regular physical exercise &training can have a positive effect and appears to improve functioning of the specific immunological response on human body. The effect of regular exercise on the © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 13–20, 2020. https://doi.org/10.1007/978-981-15-3270-2_2
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specific immune response has been received very little evidence to suggest clinical significance and many questions are still reaming. Several reports have indicated that, exercise and training produce significant increase in specific immune components (Cordova et al. 2010; Grazzi et al. 1993; Karpinski et al. 2001; Krebs 1992; Miles et al. 2003; Kendall et al. 1990; Malm et al. 2004). Though there are also evidences that regular physical activity had negative effect on specific immune parameters in response to exercise (Ramel et al. 2003; Wu et al. 2004; Nehlsen-Cannarella et al. 1991; Weiss et al. 1995; Brown et al. 2015). Research findings also showed that no changes in the specific immune variables over the exercise training (Shimizu et al. 2011; Buyukyazi et al. 2004; Barriga et al. 1993; Bachi et al. 2015; Gleeson et al. 2000; Karacabey et al. 2005). With this brief background the specific objective of the present study was to observe the effect of regular moderate exercise on selected specific immune variables in active trainees.
2 Materials and Methods 2.1
Study Area and Subjects
The city of Burdwan (Latitude 22° 56′-23° 53′ North, Longitude 86° 48′-88° 25′ East) West Bengal, India was selected as study location which is a less air polluted area in India. Total thirty two (32) male subjects were selected out of which 18 postgraduate students (Mean Age: 25 ± 2.06 yrs) from the Department of Physical Education, Burdwan University participated in this study, pursuing regular curriculum of Physical Education classes during the two previous years treated as Moderately Trained (MT) group and 14 residential students (Mean Age: 22.525 ± 1.79 yrs) from other stream such as Zoology, Chemistry, Physics, History, Bengali & Political Science were chosen as Sedentary Control (SC) group. None of the subjects had the history of smoking, drink alcohol, or were taking medication may alter the measureable variables and affect the hormonal response. 2.2
Physical Activity Programme
Moderately trained group subject trained daily in two sessions, a morning session that consisted of a 2 h practical workout of major games & sports with conditioning and an afternoon session consisting of a 2 h game practice. Cardio-respiratory fitness efficiency were assessed to maintain the homogeneity of the subjects. Resting heart rate varied 57 ± 4.80 beats/minute and exercise heart rate varied 142 ± 9.10 beats/minute. The range of resting respiratory rate was 16 ± 3.84 breaths/minute and exercise respiratory rate was 26 ± 5.56 breaths/minute. All subjects followed a similar and controlled diet throughout the session and they belong to families with very similar
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background of demographic status like socioeconomic, sociocultural, nutritional, psycho physiological and educational. The details of the training protocol in presented in the Table 1.
Table 1. Detail programme of physical activity followed by the training Days Monday
Tuesday
Wednesday
Thursday
Friday
2.3
Morning Session Practical Class (6.30 am to 8.30 pm) General conditioning (30 min) Athletic class on running (45 min) Mass demonstration class (45 min) General conditioning (30 min) Gymnastic class (45 min) Mass demonstration class (45 min) General conditioning (30 min) Athletic class on running (45 min) Mass demonstration class (45 min) General conditioning (30 min) Gymnastic class (45 min) Yoga class (45 min) General conditioning (30 min) Aerobics class (45 min) Yoga class (45 min)
Afternoon Session Practical Class 3.30 pm to 5.30 pm Major game practice (football/volleyball/kabaddi) Major game practice (basketball/handball/kho kho) Major game practice (football/volleyball/kabaddi) Major game practice (basketball/handball/kho kho) Formal and mass demonstration activities
Experimental Design
For selection of the subjects, simple random sampling was adopted. The subjects were part of a demographic comparative study design with moderately trained and sedentary control groups to determine the influence of regular moderately training and recreational activities on specific immune response. The study design is presented in the Fig. 1.
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Target Population (Regular Training Participants)
Sampling (Convenient Sampling)
Moderately Trained Group
Sedentary Group
Training Group (Male) N= 18 (Mean age 25±2.06 yrs.)
Control Group (Male) (Age sex matched) N= 14 (Mean age 22.5±1.79 yrs.)
(Process for data analysis)
Fig. 1. Flow chart of the study design
Subjects were selected according to the formulation of objectives of the study. The experiments were done only in the regular moderate training group and compared it with the regular recreational activity group as sedentary control to draw final findings. The researcher had collected blood samples and measured all the specific immunological health variables in a standard laboratory (namely Future Health Care, Kolkata, India) which is licensed under the West Bengal Clinical Establishment Act 1950. Before collecting the measurements, all the testing procedure was duly calibrated on time. Since the test of all the above specific immunological health variables were conducted in a reputed pathological research laboratory, reliability of data was established automatically. The test procedures are all valid since the methods adopted were from standard literature. 2.4
Variables Studied
To fulfill the objective of the study, two types of variables i.e. immunological and biochemical variables were assessed.
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Immunological Variables: CD4 (Helper T cells) Percentage, CD4/CD8 ratio and immunoglobulin G (IgG) were considered as immunological health variables (BD FACS Canto II automated 6 color Flow Cytometer using canto clinical software-Flow Cytometry single platform technology and COBAS e 411). Biochemical Variable: Albumin (Alb) and Albumin Globulin ratio (Alb/Glo ratio) were considered as biochemical health variables (COBAS-400). All the variables were measured from serum. 2.5
Ethical Consideration
The experimental protocol was reviewed according to the declaration of the Chief Medical Superintendent and approved by the members of the Institutional Bio-Ethics Committee of Jadavpur University, Kolkata-700032, West Bengal, India. The body is a registered (Reg. No. ECR/93/Indt/WB/2013) committee under the rule 122DD of the Drugs & Cosmetics rules 1945. All subjects were informed about the risks and signed an informed consent form for this study. 2.6
Statistical Analysis
Mean, Standard deviation and independent ‘t’ test were used for statistical analysis of the data. The differences between the means of moderately trained and control group were compared using independent ‘t’ test for unequal subjects. The differences were considered significant when the P-values were < 0.05. Data analysis and calculations were done by the computer using IBM SPSS 20.0 version software.
3 Results In the present study, the higher mean were observed in Moderately Trained (MT) group compared to Sedentary Control (SC) group in all specific immune variables although there was no significant difference found between both groups which are given in the Table 2. The higher average of IgG was observed in the MT group than the SC group (Cordova et al. 2010; Saygin et al. 2006; Martins et al. 2009; Umeda et al. 2008). The mean values of CD4% and CD4/CD8 ratio found higher in the MT group compared to the SC group (Karpinski et al. 2001; Grazzi et al. 1993; Miles et al. 2003; Pizza et al. 1995; Bauer and Weisser 2002). The MT group showed slightly higher value of Albumin and Albumin/Globulin ratio than the SC group (Krebs 1992).
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Table 2. Comparisons of means (independent ‘t’ test) between moderately trained and sedentary control group of specific immunological variables Variables IgG (mg/dL)
Groups Mean value Mean difference t-ratio Sig. (2-tailed) MT 1642.20 59.74 .716 .479 SC 1582.45 CD4 Percentage (%) MT 32.91 1.31 .567 .575 SC 31.60 CD4/CD8 ratio MT 1.20 .015 .098 .922 SC 1.19 Albumin (gm/dL) MT 5.04 .086 1.049 .303 SC 4.95 Alb/Glo ratio MT 2.00 .110 1.392 .174 SC 1.89
4 Discussion In essence, the immune system is enhanced during moderate exercise. Moreover, regular, moderate exercise can prevent the neuroendocrine and detrimental cellularimmunologic effects of various stresses. In contrast to the beneficial effects of moderate exercise on the immune system, strenuous, intense exercise or long duration exercise is followed by impairment of immune system. Two pathways link the brain and the immune system: the autonomic nervous system and neuroendocrine outflow via pituitary. Immune response alters neural and endocrine functions, and in turn, neural and endocrinal activity modifying immunologic functions. Many regulatory peptides and their receptors previously thought to be limited to the brain or to the immune system are now known to be expressed by both. It has been shown that communication between the central nervous system (CNS) and the cellular-immune system is bidirectional that endocrinal factors can alter immune function and that immune response can alter both endocrine and CNS response. The CNS can be involved in immune reactions arising from within the brain or in response to peripheral immune stimuli. Activated immunocompetent cells such as monocyte, lymphocyte and macrophages etc. can cross the blood-brain barrier and take up residence in the brain where they secrete their full repertoire of cytokine and other inflammatory mediators such as leukotrienes and prostaglanbius. All aspects of immune and complement cascades can occur in the brain because of these nerves – macrophage communication. The CNS modulates immune cells by direct synaptic – like contacts in the brain and at peripheral site such as the lymphocyte organs. Researchers suggest the brain can regulate immunocompetence. Much of this neuroimmuno modulation takes place through the hypothalamic – pituitary system but also through the sympathetic nervous system, the latter by the release of the catecholamine at autonomic nerve endings and from the adrenal medulla. The principal immunoregulatory organs (lympth node, thymas, spleen and intestinal peyer’s patches) are abundantly supplied by autonomic nerve fibers. Sensory neuron contains a variety of neurotransmitters and neuropeptides that can
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influence cellular-immunological function. Mechanism underlying the alterations in immunity with acute exercise related to the activation of the sympathetic nervous system which linked to altered activity of the hypothalamic-pituitary-adrenal axis that result restores optimal antibody responses including antigen specific cell mediated delayed type hypersensitivity responses. The present researcher couldn’t find any scientist those who were working to search the underlying mechanism of cellularimmunological function among general exercising healthy population.
5 Conclusion Within the limitation of the study, it may be concluded that regular moderate training habit may be increased in modulating the specific Immune response which is a possible biologic efficiency to foster the defense against disease on human health. Acknowledgements. The author is grateful to University Grant Commission (UGC), Govt. of India, for financial support. Cooperation and help extended by the Jadavpur University, Office Staff of the D.P.I., Sports Board and Future Health Care, Kolkata is thankfully acknowledged. The author is also grateful to the Department of Physical Education, The University of Burdwan for recruitment of subjects and constant support for smooth conduction of this study.
References Bachi, A.L., Sierra, A.P., Rios, F.J., Gonçalves, D.A., Ghorayeb, N., Abud, R.L., Victorino, A. B., Dos Santos, J.M., Kiss, M.A., Pithon-Curi, T.C., Vaisberg, M.: Athletes with higher VO2max present reduced oxLDL after a marathon race. BMJ Open Sport Exerc. Med. 1(1), bmjsem-2015-000014 (2015). E Collection Barriga, C., Pedrera, M.I., Mavnar, M., Mavnar, J., Ortega, E.: Effect of submaximal physical exercise performed by sedentary men and women on some parameters of the immune system. Rev. Esp. Fisiol. 49(2), 79–85 (1993) Bauer, T., Weisser, B.: Effect of aerobic endurance exercise on immune function in elderly athletes. Praxis (Bern 1994) 91(5), 153–158 (2002) Brown, F.F., Bigley, A.B., Ross, J.C., LaVoy, E.C., Simpson, R.J., Galloway, S.D.: Tlymphocyte populations following a period of high volume training in female soccer players. Physiol. Behav. 152(Pt A), 175–181 (2015) Buyukyazi, G., Kutukculer, N., Kutlu, N., Genel, F., Karadeniz, G., Ozkutuk, N.: Differences in the cellular and humoral immune system between middle-aged men with different intensity and duration of physically training. J. Sports Med. Phys. Fitness. 44(2), 207–214 (2004) Córdova, A., Sureda, A., Tur, J.A., Pons, A.: Immune response to exercise in elite sportsmen during the competitive season. J. Physiol. Biochem. 66(1), 1–6 (2010) Gleeson, M., McDonald, W.A., Pyne, D.B., Clancy, R.L., Cripps, A.W., Francis, J.L., Fricker, P. A.: Immune status and respiratory illness for elite swimmers during a 12-week training cycle. Int. J. Sports Med. 21(4), 302–307 (2000) Grazzi, L., Salmaggi, A., Dufonrs, A., Ariano, C., Colangelo, A.M., Parati, E., Lazzaroni, M., Nespolo, A., Bordin, G., Castellazzi, C.: Physical effort – induced changes in immune parameters. Int. J. Neurosci. 68(1–2), 133–140 (1993)
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Effects of Attentional Focus Among Novices and Elite Athletes in Sprinting Performance Saidatul Nur Syuhadah Mohamed Sabadri1,2(&), Jeffrey Low Fook Lee1, Shaza Mohd Shah1, Nursyaidatul Hafiza Madzlan1,2, and Maisarah Mohd Saleh2 1
Sultan Idris Education University, Tanjung Malim, Perak, Malaysia [email protected] 2 Universiti Teknologi Mara Cawangan Pahang, Jengka Campus, Bandar Tun Razak, Malaysia
Abstract. The main objective of this study was to investigate the effects of focus of attention among novice and elite athletes influenced the performance of short distance sprint (20 m) and maximum velocity speed (40 m). Sixty participants novice (n = 30) and elite (30) completed two trials for 20 m and 40 m sprint pre and post-test. Both novice and elite participants were randomly assigned to an internal focus group (IF), external focus group (EF) and control group (CONT). The IF group were focusing on component of body movement whilst EF group focusing on the movement outcomes. Then CONT group with no specific instruction. The participants involved three times per week for a month. Results shows in 20 m sprint test, there was a significant difference in IF and control group (novice) and EF, IF and CONT group (elite). While for 40 m sprint test, there was a significant different for IF and control group for novice. However, for elite athletes results shows a significant different in EF group. Overall finding indicates, adopting and external focus attention for novice and elites athletes enhance in reduction of times (second) in sprinting performance. Moreover, adopting external focus instruction resulted in shorter time (sec) among novice and elite athletes in sprinting performance. Keywords: Focus of attention
Novice Elite Sprinting
1 Introduction “Practice makes perfect” is a phrase that is often heard in the sports skill learning environment. Without practice athletes cannot be successful in their specific sports. Focusing on certain aspect of performing a sport skill is needed during training or practice to enhance performance either elite or novice athletes. In recent years, both coaches and skill acquisition researchers have been examining to develop the optimal approach to increase the performance of athletes. Coaches and practitioner continuously looking for a new strategies and techniques for their athletes and help their athletes to gain a competitive advantage. Usually these advantages are gained through strength and conditioning programs or through practice schedule design considerations (Porter and Sims 2013). © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 21–31, 2020. https://doi.org/10.1007/978-981-15-3270-2_3
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Sprinting performance is one of the skills that are important in various sports such as football, rugby, apart from the traditional events in athletics (e.g., 100, 200 and 400 m). Before an individual achieves proficiency in performing a skill, he or she goes through three stages of learning. They are cognitive, associative and finally autonomous level (Fitts and Posner 1967). Sprinting is a blue riband event in track and field sports. The skill required in sprinting involves the coordination of swinging the arms and pumping the legs, which are given maximum power. Although the techniques seem simple, coaches should become knowledgeable about the instructional strategies to help athletes for achieving optimal performance. In order to improve motor skills particularly in athletes’ performances, coaches play important roles in providing verbal instructions in which athletes’ core focus in a particular manner (Porter et al. 2010). Attentional focus is an important element either for a novice or elite athlete. This is because it can help a person succeed in his or her field of work. To optimize the performance of athletes, coaches should use the instructions to obtain feedback on a motion made by the athlete. Moreover, coaches should consider how information communicated affect athletes focus while delivering instruction to athletes is also one of the factors for improving the performance of an athlete (Porter et al. 2015). According to Porter et al. (2010), the method that is normally used to examine focus of attention instructions and augmented feedback involve providing participants with various forms of verbal cues designed to induce either an internal or external focus of attention. Attentional focus refers to what a person is thinking about a movement or activity that has been given. Besides, the focus of concentration is an important aspect in skill acquisition because it can either assist or limit an individual in mastering a specific motor skill (Schoenfeld and Contreras 2016). Besides, Magill (2011) focus of attention is defined as directing one’s attention to the specific characteristics in any activities when performing skills towards environment, or to action-preparation activities. An internal focus of attention is when a performer attends to focus on a specific body part to a specific body part during the performing of a motor skill and they tend to constrain the motor system by putting too much attention. In contrast, an external focus of attention occurs when based on the effect of movement in relation to the environment and the performer is allowed to focus on the outcome of the movement naturally (Porter and Sims 2013). Although the sprint performance is one of the fundamental skills that are required among athletes in sports, it has been often taken for granted by coaches and practitioners in ensuring their athletes acquire the skill properly. Before an individual achieves proficiency in performing a skill, he or she goes through three stages of learning. They are the verbal-cognitive, associative and finally autonomous level (Fitts and Posner 1967). At the initial verbal-cognitive level, individuals are not proficient in executing the required skill and they formed lots of questions cognitively as they are unsure of the required movement(s). At this stage, if the instructions by the coaches or practitioners were overwhelming, it will overload the memory capacity of the individuals, causing what movement scientists termed as ‘paralysis by analysis’ (Williams et al. 1999). In conjunction with the level of learning, how we process information and how regulate our behaviour includes foci of attention.
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Besides, focusing attention on externally rather than internally results in superior motor skill performance. These findings have been reported for a variety of sport skills that requiring the involvement of whole body power with related movements such as agility performance by Porter et al. (2010) and analysis revealed when participants adopting external instructions they had significantly faster movement times compared to when they followed internal attentional focus set of instructions and no instructions. In a study comparing novice and expert sprinters by Ille et al. (2013), manipulation of an instruction such as sprint start and using starting block when adopting external focus instructions (get off the starting blocks as quickly as possible, head towards the finish line rapidly and cross it as soon as possible) benefitted in terms of faster reaction and running time but not for block clearance because under external focus, participants elicited higher power on the starting blocks compared to internal focus and the results have shown that there is a greater impulse performance during the starting blocks but not in shorter time for block clearance. Finally, the effects of attentional focus were not different in novices and expert sprinters. According to Ziv et al. (2013) analysis showed attentional focus does not affect physiological responses, running economy or rating of perceived exertion when running at sub maximal velocities conditions between two groups. The instructions for external focus is (watching a video of running from the runner’s perspective), and internal focus focusing (on the movement of their legs). Results revealed that when visual feedback is showed to the runners, there was not affected when using attentional focus instructions because the visual velocity in the present study represented conditions of natural outdoor running. Once the research is done of outdoor running, it should be emphasized that the situation can be changed, visual feedback velocity feedback, changing regardless of internal or external focus.
2 Method 2.1
Participants
A total of sixty (60) undergraduate (n = 60 female) students, age (M 20.4 ± 1.56), height (M 158.1 ± 2.64), weight (M 52.2 ± 4.70) studying at the Sultan Idris Education University (UPSI) participate in the study. The participants were briefed verbally in an informative meeting and they signed an informed consent for approved by the internal research committee at the university before the study began. The protocol, potential benefits and risk associated with participation were fully explained to each subject. The criteria of the participants for novice were, inexperienced in sprinting performance, were never participated and represented school in sprint events and did not have any injuries. The criteria for elite athletes were, they would have represented their state or university and experienced in similar events.
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Instruments
Electric timing gates version (Brower Timing System) were used to record time at the 20 m and 40 m. A total of six gates was used, two at the starting line of 20 m and two at the middle of 40 m and two at the finishing line. The timing gates were set up parallel to the start, middle and finish lines, which were marked with coloured cone on a track in stadium. There was a pedal at the start line, which participants placed their hand on when they were ready to run. Once the hand left the pedal, the time started. Time was recorded to a wireless hand held device when the participant broke the laser signal at the starting line 20 m mark and again at the finish line 40 m. 2.3
Procedure
The participants performed training for four weeks before performing post test. Participants also go through retention period for one week. Besides that, participants had underwent the familiarization process of the instruction and performed the training three times per week for four weeks. The training program included the attentional focus instructed by the researcher for each group. Before performing the training program, the participants in each group performed pre test as a baseline measure to prevent outliers among participants. The participant was given two trials for pre and post test. During the pre test, the participants simply told by the researcher to sprint and completed the 40 m without any attentional focus. After the pre test, the participants had been randomly assigned into groups which are internal focus, external focus and control. Each participant for novice, elite and control, obtained different cues. For external focus group they received an instruction “When hear the word ‘go’, take off, look at the target and run as fast as possible”. While for the internal focus condition they were told “When you hear the word ‘go’, push through your hips, lift your knees high and swing your arms fast”. While for control group is “Run as fast as you can” which no specific attentional focus were given. Participants begin the training program on the next day. The test was conducted located at the Track and Field stadium of UPSI. The same five minutes dynamic warm up, high knees, lunges, power skip and 5 sprints follow with jogging before the pre and post test for 20 m and 40 m sprint.
3 Result All data that has been collected was analyzed by using the Statistical Packages for Social Sciences (SPSS) version 20. The individual characteristics such as age, height and weight were presented through Descriptive Statistics. Analysis of Variance with repeated measures on the second factor was used and presented through analysis of a five group (External focus group (EF), Internal Focus group (IF), Control group (CONT) 2 test (Pre, Post) with repeated measures on the second factor that use in this study to measure the variables (internal and external focus) and looking differences
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between pre and post-test for 20 m and 40 m sprint that have been done and to protect from excessive risk of a Type I error in situations where a study is comparing more than two population means. The sample size was determined by Krejcie and Morgan (1970) Post – hoc analysis also used in statistical analysis for the comparison between group and from pre to post test. Significant level were set at p < 0.05. 20 m Sprint Performance ANOVA statistical analysis 5 groups’ 2 tests with repeated measures on the second factor. From the tests of between-subjects effects shows that there was a significant difference in 20 m performance in overall between the five groups which are IF novice, EF novice, CONT, IF elite and EF elite F (4, 55) = 5.426, p = .001 (p < .05). The test of within-subjects effects shows that there is a significant effect for 20 m test; F (1, 55) = 18.912, p < .05. There was a significant interaction between group and test with 20 m sprint F (1, 55) = 23.243, p < 0.05 (Fig. 1).
20 Metre(Novice) 4.6 4.4 Time(s)
4.2 4 3.8 3.6 3.4 3.2
EF
IF
CONT
PRE
3.84
4.25
4.37
POST
3.77
4.45
4.52
Fig. 1. 20 m sprint test from pre to post test for novice athletes.
There was a significant difference in pre test among novice athletes in IF group (M = 4.25 s ± 0.22), and CONT group (M = 4.37 ± 0.40) in 20 m sprint. Similar result was found in post test for IF group (M = 4.45 s ± 0.23), and CONT group (M = 4.52 s ± 0.41). However there was only EF groups shows reduction (sec) in time from pre (M = 3.84 s ± 0.43) and post (M = 3.77 s ± 0.38) (Fig. 2).
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Time(s)
20Metre (elite) 3.9 3.85 3.8 3.75 3.7 3.65 3.6 3.55 3.5 3.45 3.4
EF
IF
CONT
PRE
3.81
3.55
3.62
POST
3.63
3.81
3.84
Fig. 2. 20 m sprint test from pre to post test for elite athletes
While for elite athletes in 20 m sprints performance results indicates a significant differences in pre test for IF (M = 3.55 s ± 0.35), EF (M = 3.81 s ± 0.21) and CONT (M = 3.62 ± 0.33). The same results was found in post test for IF (M = 3.81 s ± 0.43), EF (M = 3.63 s ± 0.23) and CONT (M = 3.84 ± 0.34). Although, the same results was found for the three groups, but, only EF groups shows reductions in time (sec) from pre (3.81 s) and post (3.63 s). 40 m Sprint
40 Metre (Novice) 9.5 Time (s)
9 8.5 8 7.5 7
EF
IF
CONT
PRE
8.02
8.43
8.54
POST
7.9
8.77
8.98
Fig. 3. 40 m sprint test from pre to post test for novice athletes
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The tests of between-subjects effects for 40 m sprint test and the test shows that there is a significant difference in 40 m performance in overall between the five groups; IF novice, EF novice, CONT, IF elite and EF elite F (4, 55) = 5.641, p = .001 (p < .05). The test of within-subjects effects shows that there is a significant effect for 40 m test; F (1, 55) = 5.557, p = .022 (p < .05). There is also a significant interaction between the five groups, F (4, 55) = 18.010, P = .000 (p < .05) (Fig. 3). There was a significantly different among novice group in pre test for IF group (M = 8.43 s ± 0.35), and CONT group (M = 8.54 s ± 0.81). Similar results was found in post test for IF group (M = 8.77 s ± 0.37) and CONT group (M = 8.98 s ± 0.97). However, there was reduction in time (sec) was found in EF group from pre (M = 8.02 s ± 1.16) and post test (M = 7.90 s ± 1.15) (Fig. 4).
40 Metre (Elite) 7.6
TIME(s)
7.4 7.2 7 6.8 6.6 6.4
EF
IF
CONT
PRE
7.47
6.82
7.17
POST
7.14
7.02
7.29
Fig. 4. 40 m sprint test from pre to post test for elite athletes
While, the EF elite group show a significant increase in time from pre to post test of 40 m, pre test(M = 7.47 s ± 0.53), and post test (M = 7.14 s ± 0.52) compared to IF group, pre (M = 6.82 s ± 0.79), post test (M = 7.02 s ± 0.82) and CONT, pre (M = 7.17 s ± 0.58), post test (M = 7.29 ± 0.57). A mixed between-within subjects analysis of variance was conducted to assess the effect of attentional focus on 40 m sprint test among IF novice, IF elite, EF novice, EF elite and CONT group. There was a significant difference between five groups F (4, 55) = 5.641, p = .001 (p < .05) and there were significant difference between pre and post-test for each groups F (4, 55) = 18.010, p = .000 (p < .001). The post hoc Bonferroni conducted shows that the lowest improvement in post test was group IF novice, followed by control group and IF elite. However there was a significant difference was found in EF group (elite) in 40 m sprint test from pre
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(M = 7.47 s ± 0.53) and post test (M = 7.14 s ± 0.52), IF (novice) pre (M = 8.43 s ± 0.35) post (M = 8.77 s ± 0.37) and CONT group pre (M = 7.17 s ± 0.58) and post test (M = 7.29 s ± 0.57).
4 Discussion The purpose of this study was to comparing the effect of attentional focus either internal or external focus of attention can be more beneficial to the novice and elite athletes in sprinting performance. Besides, it is to monitor if there were any significant differences on their 20 m and 40 m sprint start after receiving the different attentional focus instructions. In order to do this, each group completed two trials of the given task under each of the three conditions (i.e. external, internal and control,). Based on Fitts and Posner (1967), three stages of learning model, before an individual achieves proficiency in performing a skill, he or she goes through three stages of learning. They are the verbal-cognitive, associative and finally autonomous level they are the verbalcognitive, associative and finally autonomous level (Fitts and Posner 1967). At the initial verbal-cognitive level, individuals are not proficient in executing the required skill and they formed lots of questions cognitively as they are unsure of the required movement(s). At this stage, if the instructions by the coaches or practitioners were overwhelming, it will overload the memory capacity of the individuals, causing what movement scientists termed as ‘paralysis by analysis’ (Williams et al. 1999). Besides, novices would more beneficial from internal focus of attention instructions and emphasize dynamic movements rather than external focus of attention instructions. However, based on the study by Wulf (2012) novice and expert groups lead to shorter reaction times and running time in the external focus condition compared to internal focus condition. The results of current study for 20 and 40 m sprint test did not support the previous research involving external focus condition improved performance among novice athletes. The current findings are consistent with Lawrence et al. (2011) study. In that study, researchers focused on novice gymnast attentional focus. Although current findings shows no significant different in EF group (novice) but only EF shows reductions in time from pre test (3.81 s) to post test (3.63 s). There must be complicated to the novice athletes (internal) focus group to follow and understand the instruction that was given by the researcher which is focus directed towards components of body movement compared to the external focus which indicates only to the effect of the action. According to Lawrence et al. (2011) novice athletes need to attend step by step process of the skill since they not yet automatic and cannot be disrupted through conscious control. Conclusion drawn from the present study for 20 m (novice) suggest that adopting external focus of attention when performing acquisition sports skills among novice athletes does not resulted in any performance benefits. These findings may be due to the complexity of the instruction for them to follow and remember each wording that was given. However, for elite athletes result shows group from internal and external focus condition, there was a significantly difference reported between the pre and post test. The findings of the current study is in line with previous study which comparing novice
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and expert sprinters by Ille et al. (2013), manipulation of an instruction such as sprint start and using starting block when adopting external focus instructions (get off the starting blocks as quickly as possible, head towards the finish line rapidly and cross it as soon as possible) benefitted in terms of faster reaction and running time but not for block clearance because under external focus, participants gave higher power on the starting blocks compared to internal focus and the results have shown that there is a greater impulse performance during the starting blocks but not in shorter time for block clearance. Finally, the effects of attentional focus were not different in novices and expert sprinters. This finding due to the how the athletes received the instruction because when it comes to the elite athletes they was automatically process the instruction and they are familiar with the instructions relating to sprint performance and make it easier for them to follow any instructions given by the researcher. In addition, for 40 m sprints performance, this study showed that there were significant differences from pre to post test among groups IF (novice), EF (elite) and CONT group. Even though there was no previous study on 40 m in attentional focus but current study for EF (elite) study in line with Porter et al. (2012), which was significantly decreased in time with 20 m sprint test in an external focus condition (i.e., scrape the ground with the shoes), rather than internal focus condition (i.e., moving the legs and feet down and back as fast as possible) or control condition (i.e., running as fast as possible). Although EF (novice) did not show a significant difference, but the results shows slightly reduction of time from pre (8.02 s) to post test (7.9 s). A related study in swimming also found that external focus of attention also may increase swim speed performance. The results indicates that, external focus group significantly decreased in time when they focusing on pushing the water back (external focus) compared when asking them to focusing on pulling their hands back (internal focus) or not giving any instructions (Freudenheim et al. 2010). Besides that, current study also supported by previous study according to Porter and Sims (2013) stated that elite athletes should not be instructed to focus internally or externally on the task when performing a short distance sprint because highly trained athletes may interrupts the process of procedural knowledge and the motor control processes associated with working memory when adopting with internal and external focus of attention. However, based on current study, there was a significantly different for external focus in 40 m sprint for elite athletes. A result meets the criteria of track and field event because in track and field event require athletes to manipulate an object (e.g., shot put, discus, and javelin) and also require the athletes to perform powerful movement (e.g., 100 m sprint, long jump and hurdling). Adopting an external focus of attention has been shown to enhance performance that are associated with the events of track and field. Besides that, external focus also enhance in maximum running velocity (40 m) for elite athletes. Current findings on 40 m sprint give new knowledge to coaches and practitioner. Overall current study indicates, adopting an external focus of instruction shown improvement in sprinting performance (sec) from pre to post test compared to adopting internal focus or no specific instruction (control) which may enhance in performance drop.
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5 Conclusion The present study is the first study which examines the effects of attentional focus among novice and elite athletes for 40 m sprint performance (stride phase). Furthermore, the current findings also clearly indicates that, adopting an external focus of attention among novice and elite athletes shows reduction in time from pre to post test. The findings of the current study is in line with previous study which comparing novice and expert sprinters by Ille et al. (2013), which manipulation of an instruction such as sprint start and using starting block when adopting external focus instructions benefitted in terms of faster reaction and running time. Generally, for novice and elite athletes, this current study may help coaches and practitioners to choose the best instruction to enhance the performance of the athletes specifically on sprinting performance. Besides, the coach must use a systematic and orderly instruction to novice athletes because they are still in a learning process that requires them to understand each of the techniques that need to be done in a particular skill. It is important to point out, novices and elites are totally different because elite athletes who already have knowledge and experience in a skill and a technique in a particular skills. This skill will lead to something that happens naturally without any interruption in mind and they can focus better when adopting external focus or no instructions given to them. Interestingly, external focus instructions not only enhance in shorts sprint (20 m) but it also helps in maximum running speed (40 m) which is called stride phase that is one of the most important distance that can make athletes achieved better time (sec) in 100 m sprint performance. In addition, coaches and practitioner also may test the athletes to determine the performance of their athletes by testing in 20 m and 40 m in other sports for example football and rugby. This is because, the sports also involving speed in the game. This may help coaches to choose a proper words and right instructions to their athletes.
References Fitts, P.M., Posner, M.I.: Human Performance. Brooks/Cole, Belmont (1967) Freudenheim, A.M., Wulf, G., Madureira, F., Corrěa, U.C., Corrěa, S.C.P.: An external focus of attention results in greater swimming speed. Int. J. Sports Sci. Coach. 5, 533–542 (2010) Ille, A., Selin, I., Do, M.-C., Thon, B.: Attentional focus effects on sprint start performance as a function of skill level. J. Sports Sci. 31(15), 1705–1712, 533, 542 (2013) Krejcie, R.V., Morgan, D.W.: Determining sample size for research activities. Educ. Psychol. Measur. 30, 607–610 (1970) Magill, R.A.: Motor Learning and Control: Concepts and Applications. McGraw-Hill, New York (2011) Lawrence, G.P., Gottwald, V.M., Hardy, J., Khan, M.A.: Internal and external focus of attention in a novice form sport. Am. Alliance Health 82(3), 431–441 (2011) Porter, J.M., Sims, B.: Altering focus of attention influences elite athletes sprinting performance. Int. J. Coach. Sci. 7, 41–51 (2013) Porter, J.M., Wu, W.F., Patridge, J.A.: Focus of attention and verbal instructions strategies of elite track and field coaches and athletes. Sports Sci. Rev. 19, 77–89 (2010a)
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Porter, J.M., Wu, W.F.W., Crossley, R.M., Knopp, S.W., Campbell, O.C.: Adopting an external focus of attention improves sprinting performance in low-skilled sprinters. J. Strength Cond. Res. 29(4), 947–953 (2015) Porter, J.M., Ostrowski, E.J., Nolan, R.P., Wu, W.F.W.: Standing long-jump performance is enhanced when using an external focus of attention. J. Strength Cond. Res. 24(7), 1746–1750 (2010b) Schoenfeld, B.J., Contreras, B.: Attentional focus for maximizing muscle development: the mind-muscle connection. Strength Cond. J. 1–3 (2016) Williams, A.M., Davids, K., Williams, J.G.: Visual Perception and Action in Sport. E.&F.N., London (1999) Wulf, G., Chiviacowsky, S.: Altering mindset can enhance motor learning in older adults. Psychol. Aging 27(1), 14–21 (2012) Ziv, G., Rotstein, A., Lidor, R., Meckel, Y.: The effectiveness of attentional instructions on running economy at a submaximal velocity. Kinesiol. J. 45(2), 147–153 (2013)
The Effects of Myofascial Release Using Foam Rolling and Resistance Band Assisted Stretching on Malaysian Rugby Players’ Lower Body Power and Flexibility Nurul Afiqah Bakar1(&), Nurul Hidayah Amir1, Ammar Md Zaini1, Luke Nikol2, and Mohd Hazwan Zikri Abdul Halim3 1
Faculty of Sports Science and Recreation, Universiti Teknologi MARA, Perlis Branch, Arau Campus, 02600 Arau, Perlis, Malaysia [email protected] 2 Faculty of Sports Science and Recreation, Universiti Teknologi MARA Sarawak Branch, Samarahan Campus, Kota Samarahan, Sarawak, Malaysia 3 Kedah Football Association, Alor Setar, Kedah, Malaysia
Abstract. Integrating warm-up and stretching prior to performing physical activities has been shown to enhance sporting performance prevent injuries. Foam rolling, also known as myofascial release is widely applied in sport settings as a warm-up. However, there is limited evidence on its effectiveness on lower body power and flexibility among ruggers. This study aimed to compare the effects of myofascial release using foam rolling (MFR) and resistance band assisted stretching (RB) on lower body power and flexibility among Malaysian rugby players. Fifteen elite Malaysian male rugby players were exposed to three warm-up routines consisted of a total body dynamic warm-up (DYN), a totalbody dynamic warm-up with foam rolling session (MFR), and total-body dynamic warm-up with resistance band assisted stretching (RB). Following general warm-up in each condition, participants performed flexibility and power tests. Differences in test results between conditions (DYN vs. MFR vs. RB) were investigated using one-way ANOVA. Findings revealed no significant differences in test results for both variables, however MFR recorded a superior performance of power relative to others. Keywords: Myofascial release
Warm-up Rugby Power Flexibility
1 Introduction Integrating warm-up and stretching prior to performing physical activities has the potential to enhance sporting performance besides its capacity to prevent injury. Preexercise routines comprises of warm-up and stretching are specifically structured to elevate body core temperature and increase muscular and blood circulation thus improving muscular performance and joints range of motion (ROM) [1]. Past researchers had reported massive benefits associated with warm-up and dynamic stretching towards neuromuscular, physiological and psychological components, as © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 32–41, 2020. https://doi.org/10.1007/978-981-15-3270-2_4
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well as lowering the risk for muscular and tendinous injury [1]. Pre-exercise warm-up has been considered as an essential part of exercise for decades. A warm-up typically consists of submaximal aerobic activity with a purpose of raising core body temperature [2]. Static stretching has been considered as part of warm-up routine for years. However, static stretching is reported to cause decrement in subsequent performance [2]. Active or dynamic warm-up, on the other hand, is preferable as it does not demonstrate any subsequent decrement in performance [3–5]. Foam rolling, also known as self-myofascial release, is one of the pre-exercise stretching approaches widely used in sport settings. Self-myofascial release using foam rolling can either be used to increase training efficiency and sporting performance as well as to hasten post-exercise recovery [6]. In the past, self-myofascial release technique was used as a method to alleviate pain and aiding in performance recovery. The integration between dynamic stretching with foam rolling and resistance band has only recently emerged as a pre-exercise routine or as an additional warm-up exercise. Current studies reported improvement in sports performance when foam rolling and resistance band routine were added to dynamic stretching [7]. Warm-up routine incorporating the use of resistance band has been implied in sport to elevate proprioceptive motor control. More recently, the popularity of resistance band as tools for performance enhancement in sports had increased tremendously [8]. The application of resistance band can be considered as a useful intervention to enhance the force capability of the musculature which leads to improvement in overall range of motion. It also serves as a tool to create resistance in performing movements throughout a range of motion with greater velocity and dynamic force generation especially in sport activities [9]. There is limited evidence on the effectiveness of self-myofascial release using foam rolling. One study reported an improvement in strength, speed, power and agility succeeding dynamic stretching combined with self-myofascial release via foam rolling group when compared to dynamic stretching alone [7]. Similarly, there are very few studies focusing on myofascial release foam rolling and resistance band as pre-exercise routine. An elastic-tension component generated from the band is postulated to change the force production during the lift thus induce neural adaptation in muscles [8]. It is not known whether pre-exercise routine using foam rolling for myofascial release using resistance band could produce positive effects in muscular performance. Therefore, this study intended to investigate and compare myofascial release via foam rolling versus resistance band routine as warm-up protocol in terms of the effects on lower body power and flexibility among Malaysia rugby players. It is hypothesized that lower body power and flexibility could be enhanced by foam rolling combined with dynamic warm-up.
2 Methods 2.1
Experimental Design
The study adopted a counterbalanced, crossover within-subjects design. Participants participated in three experimental conditions on 7-day intervals: (i) DYN: general
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warm-up followed by dynamic warm-up; (ii) MFR: general warm-up followed by dynamic warm-up with the addition of a single bout of foam rolling routine on the lower body; and (iii) RB: general warm-up followed by dynamic warm-up with the addition of resistance band assisted stretching routine on the lower body. Lower body power and flexibility were assessed following both experimental conditions. 2.2
Participants
Fifteen, male national rugby players (Table 1) participated in the study. They currently represented Malaysia in Rugby 15s and trained regularly with the national team. Throughout the duration of the study, participants were required to maintain a normal diet. In addition, participants were instructed to abstain from any form of intense physical activity, alcohol and caffeine ingestion 24 h before testing. The medical history and screening questionnaires were distributed to identify any medical contraindications for physical activity. Prior to participation in the study, participants read, agreed and signed a consent form. On test days, participants reported to the laboratory for all testing procedures. Participants were also measured for anthropometric including body weight, height and BMI. Table 1. Participant characteristics. Participants Age (years) Height (cm) Weight (kg) BMI (kg/m2) Limb length (cm) N = 15 23.9 ± 2.7 176.2 ± 6.3 99.5 ± 11.8 32.3 ± 7.2 96.2 ± 9.8
2.3
Protocol and Measurement
Each experimental condition began with general warm-up that required participants to jog 1000 m at self-selected pace. In the DYN condition, participants performed dynamic warm-up involving a variety of mobility and sport-specific movements that included arm circles, body weight squats, body weight squat jumps, high knees sprint, butt kick sprint and alternate lunge jumps. Each movement followed a 2 sets 10 repetitions/meter in the same order as adapted from Peacock [7]. A 4-min rest intervals were used between tests. In the MFR condition, following a general warm-up, participants executed a myofascial release routine using a three-dimensional (3D) surface foam roller (The GRID® Foam Roller, Trigger Point). The rolling protocol (Fig. 1) aimed at the thoracic/lumbar regions, the gluteal region, the hamstring region, the calf region from the supine body position and finally the quadriceps/flexor region. Entire surface area of each muscles group was rolled at 5 strokes per 30 s. Each rolling technique was done bilaterally thus involving both sides and limbs. Following the foam rolling routines, participants then performed the same dynamic warm-up involving a variety of mobility and sport-specific movements as described in DYN protocol.
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Fig. 1. MFR lower body foam rolling progression order includes A - thoracic/lumbar, B gluteal, C - hamstring, D - calf, E - quadriceps/flexor regions. Taken for rolling demonstration purposes only (adapted from Peacock et al. [7])
In the RB condition, participants were instructed through a resistance band assisted stretching using mini resistance band (PNF BANDS) following a general warm-up. Resistance band assisted stretching exercise (Fig. 2) consisted of squat, hip extension, hip flexion, hip abduction, and side-to-side walking for both legs. Each exercise was executed in 2 sets 10 repetitions in each set.
Fig. 2. RB exercise includes A - squat, B - hip extension, C - hip flexion, D - hip abduction, E side-to-side walking. This figure taken for resistance band assisted stretching demonstration purposes only.
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Following each experimental conditions, participants were tested for lower body power and flexibility performance. To measure power, countermovement jump (CMJ) test was conducted on a force platform (Fitness Technology, Australia) based on procedures described by Bosco [10]. Only two trials were allowed per participant, with a recovery period of one minute. Participants bended their knees to a comfortable chosen angle and executed highest vertical jump from standing position with the hands fixed on the hips. Effect of arm-swing was evaded by both hands were held on the hips during the jump. Take-off was initiated from both feet with no initial steps or shuffling, and without pause at the base of the squat. Body needed to be kept erect throughout the jump to avoid inappropriate planes movements. Participants landed with knees fully extended for initial contact with the force plate, and implied soft landing by keeping the knees bends post landing. Any jump that was observed to diverge from the protocol was repeated. Results were averaged for both trials. The Y-Balance test (YBT) test was conducted to measure flexibility according to the procedure proposed by Shaffer [11]. To minimize the influence of a learning effect, participant viewed a YBT instructional video and then performed 6 practice trials. With the distal aspect of the right foot at the starting line, participants stood on the centre footplate. Participant reached the footplate with the left leg while the right leg maintaining a single leg stance. The reaching maneuvers were performed in three directions; anterior, posteromedial, and posterolateral directions relative to the stance foot by pushing the indicator box as far as possible. Participants performed three trials in each direction and the average of the distance recorded were calculated to the nearest 0.5 cm. Measurement of leg length was taken from the anterior superior iliac spine to the most distal of the medial malleolus. Reach distances were calculated as absolute reach values. Composite reach distance was the sum of the 3 reach directions divided by 3 times limb length, and then multiplied by 100%. 2.4
Statistical Analysis
Data is presented as means with standard deviations. Following Shapiro-Wilk normality testing, one-way analysis of variance (ANOVA) were used to determine if there were any significant differences on performance variables (countermovement jump peak power [watt] and Y-Balance test composite reach distance [%]) between conditions (DYN vs. MFR vs. RB). All statistical analyses were performed using SPSS for Windows (version 23, SPSS Inc.).
3 Results The CMJ and YBT test measures are listed in Table 2. The data indicated no significant differences in countermovement jump peak power and Y-Balance test composite reach for both right and left limb when compared among the three warm-up routines.
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Table 2. Performance test results. Performance variable CMJ peak power (watt) YBT composite reach right limb (%) YBT composite reach left limb (%)
DYN 7670.38 ± 489.16 130.40 ± 84.71
MFR 7918.95 ± 126.59 103.77 ± 14.52
RB 7790.18 ± 495.54 98.39 ± 12.54
107.70 ± 14.72
106.95 ± 13.88
97.47 ± 11.30
4 Discussion Foam rolling or myofascial release produce similar effects as a massage and roller massager to release the fascia. Due to its benefit in increasing tissue length and removing fibrous adhesions at the muscle fascia, foam rollers has gained its popularity as warm-up tool [12, 13]. This study was the first to compare between MFR to DYN and RB. However, it is not the first to investigate the effects of foam rolling in general. The results of this current study shows that the addition of foam rolling after a dynamic warm-up routine does not acutely improve power and flexibility. Nevertheless, the results portray that foam rolling in adjunct with dynamic stretching may provide better lower body power relative to the other warm-up protocols. This study outcome is comparable to previous studies investigating the effects of foam rolling which showed that foam rolling did not improve performance [12, 14, 15]. No significant differences were justified in these studies, despite the used of multilevel roller, rolled on different muscle groups, and used different durations of time on a particular muscle group received treatment [12, 14]. Handheld roller massage apparatus also did not show any improvement in athletic test performance [15, 16] or isometric hamstring performance [17]. In contrast, different evidence has shown that the application of a handheld roller massager improved maximal voluntary contraction of the plantar flexors post 10-min of its application when compared to static stretching [18]. However, after 1-min application of the roller massager for static stretching, there were no significant differences reported. This was confirmed in our study that performance was not affected immediately following the three implemented warm-up conditions. Investigations in divergent strokes and duration of foam rolling have demonstrated no increase in performance. Like the current study, previous investigation also used the approach of foam rolling for 30 s per muscle group [14], while different researchers used foam rolling on the quadriceps for two, 1-min bouts [12]. These findings differ from studies that have examined the acute effect of massage on performance where performance were negatively affected after five to six minutes of lower body massage [19–21]. 20-m sprint performance also negatively affected succeeding 1-min massage to the gastrocnemius, hamstrings, gluteals and quadriceps and 30 s to the tibialis anterior [22]. Negative effects of massage on isokinetic knee extensor performance were concluded that could be due to an increase in parasympathetic nervous system activity [21]. Warm-up activities sequence used in the present study did not enhance countermovement jump performance. Participants in this study had performed a standardized
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dynamic warm-up prior to foam rolling, prior to resistance band assisted stretching and control conditions. Similarly, prior to foam rolling and planking conditions, previous researchers had participants perform a standardized dynamic warm-up [14, 15] while some had participants perform a 5-min cycle ergometer warm-up prior to foam rolling and control conditions [12]. Investigations on pre-performance massage from previous studies have found that it negatively affected performance [19–22]. Others concluded that perhaps performing a warm-up after massage could minimize the negative effects [22, 23]. On average, negative effects of short-term muscular performance is due to the way of an adverse effect on either neuromuscular activation or on the length-tension relationship of the muscle [3]. Increment in muscular activation and force production succeeding myofascial release treatments would be ideal, as it could increase movement efficiency and athletic performance, but this does not appear to be as intended. However, myofascial release therapies do not decrease muscular activation or force production [24]. No changes were observed in peak power production. This is further supported by previous researchers [16] as there was no decreases in measures of athletic performance following an acute bout of self-myofascial release among National Collegiate Athletic Association Division II athletes. It would not be an effective modality prior to the start of activity if myofascial release modalities did inhibit muscular performance. Therefore, the truancy of muscular deactivation and reduction in force development succeeding myofascial release treatments is of major importance to sports medicine clinicians, strength and conditioning professionals, and athletes. Similarly, the result of YBT in this current study did not demonstrate significant acute improvement in flexibility. This finding is consistent with previous studies [7, 25] which reported no significant improvement in hamstring flexibility in following an acute bout of warm-up. However, the findings of a meta-analysis study showed that short-term improvements are expected to observe in flexibility when it is used as preexercise warm-up [6]. This statement was supported in more recent findings [12, 26] which suggested that one minute of MFR is recommended but no longer than 5 min for the improvement in muscle and joint range of motion (ROM) to occur. It was hypothesized that pressure-associated changes in myofascial property could altered the thixotropic property of fascia surrounding muscle when the pressure applied via foam rolling is greater than the physical range of muscle [26]. This change is possible if the pressure or heat is applied, and within minutes before the substance returns to its original state of colloidal substances (gel-like state) [6, 26]. However, this theory was not observed in the present study. On the contrary, chronic application of MFR in some studies is proven to be beneficial. The current study only performed one session of MFR protocol. It was reported that three bouts of 1-min MFR protocol applied as intervention for duration of 2-weeks for six sessions [29], 4-weeks [28] and 8-weeks interventions [25] showed a significant improvement in hamstring flexibility as opposed to other in which reportedly include heterogeneity of participants’ nature and uncontrolled testing time of the day [25]. It is suggested that future study to include multiple session of MFR. It was demonstrated that flexibility is dependent on time of day testing with flexibility deemed to be greatest in the evening [27, 28]. It is assumed that the current study did not show significant improvement in flexibility as testing for all exposure was
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conducted between 10 to 11 in the morning. Hence, it is suggested that the flexibility testing time in future investigation to be performed in the evening as it is essential to yield maximum results and simultaneously minimize bias and errors. The selection of participants also seems to be another debatable factor between untrained and well-trained athletes which could greatly influence the result. The present study has utilized Malaysian Rugby athletes as recruited participants with no significant flexibility improvement. The finding of this study is consistent with previous study which postulated that well-trained athletes with normal muscle range of motion is most likely to reach a ceiling effects which in turn did not demonstrated significant increase in ROM [16]. In a study comparing the chronic effects of static stretching in trained versus untrained individuals, greater improvement was reported in untrained individuals [30]. There were possible limitations of the current study and some of it were the type of foam rollers used, and the duration and strokes of rolling that can be corrected in future studies. Selection of trained or untrained participants should also be considered in detail. Moreover, future studies can investigate the effects of myofascial release using foam rolling (MFR) and resistance band (RB) routine effects on recovery phase such as after training and the off-season’s effects. Myofascial release and resistance band could be considered when implementing the most efficient training routines and might improve athletic performance. Psychological effects and outcomes can be implemented for future studies as well.
References 1. Park, H.K., Jung, M.K., Park, E., Lee, C.Y., Jee, Y.S., Eun, D., Cha, J., Yoo, J.: The effect of warm-ups with stretching on the isokinetic moments of collegiate men. J. Exerc. Rehabil. 14 (1), 78 (2018) 2. Christensen, B., Napoli, R., Hackney, K., Miller, J., Murata, H.: The effects of two different types of dynamic warm-up and static stretching on power and speed. In: ISBS-Conference Proceedings Archive, pp. 247–250 (2016) 3. Behm, D.G., Chaouachi, A.: A review of the acute effects of static and dynamic stretching on performance. Eur. J. Appl. Physiol. 111(11), 2633–2651 (2011) 4. Holt, B.W., Lambourne, K.: The impact of different warm-up protocols on vertical jump performance in male collegiate athletes. J. Strength Cond. Res. 22(1), 226–229 (2008) 5. McMillian, D.J., Moore, J.H., Hatler, B.S., Taylor, D.C.: Dynamic vs. static-stretching warm up: the effect on power and agility performance. J. Strength Cond. Res. 20(3), 492–499 (2006) 6. Wiewelhove, T., Döweling, A., Schneider, C., Hottenrott, L., Meyer, T., Kellmann, M., Pfeiffer, M., Ferrauti, A.: A meta-analysis of the effects of foam rolling on performance and recovery. Front. Physiol. 10, 376 (2019) 7. Peacock, C.A., Krein, D.D., Silver, T.A., Sanders, G.J., Von Carlowitz, K.P.A.: An acute bout of self-myofascial release in the form of foam rolling improves performance testing. Int. J. Exerc. Sci. 7(3), 202 (2014) 8. Bellar, D.M., Muller, M.D., Barkley, J.E., Kim, C.H., Ida, K., Ryan, E.J., Bliss, M.V., Glickman, E.L.: The effects of combined elastic-and free-weight tension vs. free-weight tension on one-repetition maximum strength in the bench press. J. Strength Cond. Res. 25 (2), 459–463 (2011)
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9. Janusevicius, D., Snieckus, A., Skurvydas, A., Silinskas, V., Trinkunas, E., Cadefau, J.A., Kamandulis, S.: Effects of high velocity elastic band versus heavy resistance training on hamstring strength, activation, and sprint running performance. J. Sports Sci. Med. 16(2), 239 (2017) 10. Bosco, C., Komi, P.V., Tihanyi, J., Fekete, G., Apor, P.: Mechanical power test and fiber composition of human leg extensor muscles. Eur. J. Appl. Physiol. 51(1), 129–135 (1983) 11. Shaffer, S.W., Teyhen, D.S., Lorenson, C.L., Warren, R.L., Koreerat, C.M., Straseske, C.A., Childs, J.D.: Y-balance test: a reliability study involving multiple raters. Mil. Med. 178(11), 1264–1270 (2013) 12. MacDonald, G.Z., Penney, M.D., Mullaley, M.E., Cuconato, A.L., Drake, C.D., Behm, D.G., Button, D.C.: An acute bout of self-myofascial release increases range of motion without a subsequent decrease in muscle activation or force. J. Strength Cond. Res. 27(3), 812–821 (2013) 13. Barnes, M.F.: The basic science of myofascial release: morphologic change in connective tissue. J. Bodyw. Mov. Ther. 1(4), 231–238 (1997) 14. Healey, K.C., Hatfield, D.L., Blanpied, P., Dorfman, L.R., Riebe, D.: The effects of myofascial release with foam rolling on performance. J. Strength Cond. Res. 28(1), 61–68 (2014) 15. Jones, A., Brown, L.E., Coburn, J.W., Noffal, G.J.: Effects of foam rolling on vertical jump performance. Int. J. Kinesiol. Sports Sci. 3(3), 38–42 (2015) 16. Mikesky, A.E., Bahamonde, R.E., Stanton, K., Alvey, T., Fitton, T.: Acute effects of the stick on strength, power, and flexibility. J. Strength Cond. Res. 16(3), 446–450 (2002) 17. Sullivan, K.M., Silvey, D.B., Button, D.C., Behm, D.G.: Roller-massager application to the hamstrings increases sit-and-reach range of motion within five to ten seconds without performance impairments. Int. J. Sports Phys. Ther. 8(3), 228 (2013) 18. Halperin, I., Aboodarda, S.J., Button, D.C., Andersen, L.L., Behm, D.G.: Roller massager improves range of motion of plantar flexor muscles without subsequent decreases in force parameters. Int. J. Sports Phys. Ther. 9(1), 92 (2014) 19. Arabaci, R.: Acute effects of pre-event lower limb massage on explosive and high speed motor capacities and flexibility. J. Sports Sci. Med. 7(4), 549 (2008) 20. Arazi, H., Asadi, A., Hoseini, K.: Comparison of two different warm-ups (static-stretching and massage): effects on flexibility and explosive power. Acta Kinesiol. 6(1), 55–59 (2012) 21. Arroyo-Morales, M., Fernández-Lao, C., Ariza-García, A., Toro-Velasco, C., Winters, M., Díaz-Rodríguez, L., Cantarero-Villanueva, I., Huijbregts, P., Fernández-De-las-Peñas, C.: Psychophysiological effects of preperformance massage before isokinetic exercise. J. Strength Cond. Res. 25(2), 481–488 (2011) 22. Fletcher, I.M.: The effects of precompetition massage on the kinematic parameters of 20-m sprint performance. J. Strength Cond. Res. 24(5), 1179–1183 (2010) 23. Goodwin, J.E., Glaister, M., Howatson, G., Lockey, R.A., McInnes, G.: Effect of preperformance lower-limb massage on thirty-meter sprint running. J. Strength Cond. Res. 21(4), 1028 (2007) 24. Mauntel, T.C., Clark, M.A., Padua, D.A.: Effectiveness of myofascial release therapies on physical performance measurements: a systematic review. Athl. Train. Sports Health Care 6 (4), 189–196 (2014) 25. Miller, J.K., Rockey, A.M.: Foam rollers show no increase in the flexibility of the hamstring muscle group. UW-L J. Undergrad. Res. 9, 1–4 (2006) 26. Phillips, J., Diggin, D., King, D.L., Sforzo, G.A.: Effect of varying self-myofascial release duration on subsequent athletic performance. J. Strength Cond. Res. (2018)
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27. Guariglia, D.A., Pereira, L.M., Dias, J.M., Pereira, H.M., Menacho, M.O., Silva, D.A., Cyrino, E.S., Cardoso, J.R.: Time-of-day effect on hip flexibility associated with the modified sit-and-reach test in males. Int. J. Sports Med. 32(12), 947–952 (2011) 28. Junker, D.H., Stöggl, T.L.: The foam roll as a tool to improve hamstring flexibility. J. Strength Cond. Res. 29(12), 3480–3485 (2015) 29. Mohr, A.R., Long, B.C., Goad, C.L.: Effect of foam rolling and static stretching on passive hip-flexion range of motion. J. Sport Rehabil. 23(4), 296–299 (2014) 30. Beardsley, C., Škarabot, J.: Effects of self-myofascial release: a systematic review. J. Bodyw. Mov. Ther. 19(4), 747–758 (2015)
The Effects of High Intensity Functional Interval Training on Selected Fitness Components Among Young Badminton Players Pathmanathan K. Suppiah1, Angelica Joanne Joummy1(&), Md. Safwan Samsir1, Muralindran Mariappan2, Hasnol Noordin1, and Abdul Mu’iz Bin Nor Azmi1 1
Faculty of Psychology and Education, University Malaysia Sabah, Kota Kinabalu, Sabah, Malaysia [email protected] 2 Faculty of Engineering, University Malaysia Sabah, Kota Kinabalu, Sabah, Malaysia
Abstract. The main objective of this study was to measure the effect of high intensity functional interval training on aerobic fitness, agility and sprint among young badminton players. A total of 16 male badminton players aged between 13 and 15 years old volunteered for this study. Participants were randomly divided into two groups, Experiment (n = 8) and Control (n = 8) based on aerobic fitness assessment result. The Experimental group (EG) performed a high intensity functional interval training exercise while the Control group (CG) performed traditional training whereby a routine exercise that was usually carried out in their training program over a period of 10 weeks. The high intensity functional interval training consisted of change of direction (COD) elements where the athlete moved to respond to a sound stimuli that was activated by a wireless sensors. The training intensity was 80–95% HRmax; work-to-rest ratios of each repetition is 1:1 (3 min work: 3 min rest) 2 sets training (with had 5 repetitions per set) and rest between each set of training is 4 min. Data was collected at three-time points; T1pre, T2-post five weeks and T3-post ten weeks training. Repeated measures mixed ANOVA yielded significant interactions over time in the performance of the 20 m Multistage Fitness; Four Corner Agility and Sprint 20 m. The results show that there were a significant difference between EG and CG for 20 m Multistage Fitness and Four Corner Agility; F(1,14) = 4.663, (p < .05) and F(1,14) = 5.443, (p < .05). Whereas no significant different for sprint performance; F(1,14) = .351, _ 2max and (p > .05) between the EG and CG. In conclusion, the EG showed VO agility performance increased significantly after 10 weeks of high intensity functional interval training without negatively influencing the sprinting ability. Keywords: High intensity functional interval training _ 2max VO
Traditional training
1 Introduction Badminton is a combination of high-intensity short rallies (anaerobic system) and longer rallies (aerobic systems), with short recovery between rallies [1]. Researchers have observed that a badminton player obtain 60–70% of the energy from aerobic system and © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 42–53, 2020. https://doi.org/10.1007/978-981-15-3270-2_5
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30% is from anaerobic system [2, 3]. The time period of badminton match is between 15–90 min depending on the player’s performance and the number of rallies played [4]. Badminton players require high levels of both aerobic energy towards maintaining performance for a duration of half an hour or more. Hence, the competitive badminton players’ training should concentrate on improving their ability to repeat a high-intensity activities and faster recovery after that. Therefore, aerobic fitness improvement should be included in the badminton training as one of the physical exercise [5]. The effect of HIIT programs especially among young players badminton field is little known. HIIT is defined as either repeated short ( .05). All participants were healthy, free from any chronic health conditions and no hearing problems. The Physical Activity Readiness Questionnaire (PAR-Q) was administered to the subjects prior to participation to rule out contraindications to participation. This study was approved by the University Malaysia Sabah Ethics Committee (JKEtika 4/17 (3)) and Malaysia Education Ministry (KPM.600-3/2/3-eras(1864)). Table 1. Participants’ characteristics HIIT CON Age (y) 13.50 + .46 13.25 + .93 Weight (kg) 47.55 + 3.7 48.96 + 5.7 Height (cm) 158.96 + 4.8 160.04 + 6.9
2.3
Procedures
Laboratory Measurements 20 m Multistage Fitness. The 20 m multistage fitness categorized as a field test to determine aerobic fitness. This field test shown to be one of an aerobic power which has a reliable and valid indicators [13, 14]. The 20 m multistage fitness test comprises of shuttle running at consistent increase speeds between 2 markers which located at
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20 m apart, according to the pace of the recorded beeps. Participants however were needed to reach at one end of 20 m course before the beep signals. A student participants was required to maintain a start speed of 8.5 km/h for a minute, then increase to 0.5 km/h for every minute. The test score achieved was the number of 20 m laps completed before the participant either failed to arrive within 3 m of the line on two consecutive tones or withdrew voluntarily from the test. The maximum rate of oxygen _ 2max was measured according to the norm [15]. consumption VO Four Corner Agility. The four corner agility is a test to determine agility fitness. This agility test was once performed at one side of a badminton court placing and forward/diagonal four-corner actions with abrupt changes in direction (Fig. 2) [16]. In order to complete the four-corner agility test, players need to move around the four corners of the court for 16 repetitions in total. Then, players need to follow the sequence order of four directions, while striking each of the up - turned shuttlecocks located at each corner (Fig. 2). The adhere of badminton - specific movements are being remind to players by moving towards the direction of their dominant hand (racket - holding hand) for a start; then followed by striking the up - turned shuttlecock also with their dominant hand. A best performance time will be recorded at a minimum of two trials. Participants were allowed to take recovery for 5 min between trials.
Fig. 2. The set-up for the four corner agility test on court. Sideways agility, order of movement (right-handed) = Central Base – A – Central Base – B – Central Base – C – Central Base – D – Central Base, or (left-handed) = Central Base – C – Central Base – D – Central Base A – Central Base – B – Central Base, and repeat until the player strikes each of the 16 shuttlecocks.
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20 m Sprint. The 20 m sprint test is used to determine sprint fitness among participants. Participants were prepared at the start of the line with split-stance start position. (Note: the participants were instructed to use the same starting stance for the reliability). At the signal of “GO”, student participants needed to sprint at maximal level towards finishing line as quickly as possible. Each badminton player completed 20 m sprint interspersed for 3 times with a passive recovery for 3 min. The fastest time achieved was recorded. Training Protocol High Intensity Functional Interval Training. The participants trained 3 times per week over an 10-weeks training period, resulting in 30 training sessions. Both training interventions were performed on court, separated by at least 48 h. The training program consisted change of direction (COD) elements where the athlete moved in response to the sound stimuli that was activated by wireless sensors (Fig. 3). The EG players stood with a racket in a frontal position in the middle of the court. Upon hearing a signal, the player turned sideways and ran to beacon to intercept ultrasound wave and return to the middle of the court. The movement of this exercise training replicated the tactical movements in badminton (i.e., side steps, lunges & etc…). The movement patterns were controlled by a computer program UMS ATAC 1.1. The researcher keyed in the biodata of the participants and used the random training mode. The participants responded to all the locations in one loop and the duration of each set was 3 min. The delay between the auditory signal was set at 1 s (Fig. 4).
Fig. 3. The arrangement of the sensors on court.
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Fig. 4. The badminton program system for high intensity functional interval training.
Resting heart rate (HR) was taken prior to every training session. Resting HR was the minimal value of HR attained for 3 consecutive interval times after 10 min participants were in a quiet room on a mat in the supine positions, with their eyes closed [17]. Target HR training was determined using the Karvonen protocol. The EG performed 2 sets of training and each of the set consisted of 5 repetitions. The rest period between each set was 4 min. The duration of each repetition was 3 min at an intensity of 80–95% HRmax and the rest period of 3 min between repetitions. During recovery period participants performed a low intensity activity that was below 60% HRmax. Total training duration excluding (warming up = 10 min and cooling down = 15 min) was 30 min of HIIT and 28 min of active recovery. On average within 3 min interval, participants completed 87 to 100 movements on court. During the training the participants wore monitors (polar RCX3) to monitor their heart rate. The researcher held the watch (polar RCX3) and stand outside the line of badminton court to ensure the participants achieve the training intensity 80–95% HRmax. The data obtained from the HR monitors were downloaded on portable personal computer using the manufacture’s software. HR data were classified based on beat per minute spent in 5 zones: (a) 100–119 bpm, (b) 120–139 bpm, (c) 140–159, (d) 160–179, (e) 180–200. Individual average duration and intensity of these periods were calculated. Figure 6 shows the percentage of time spent by the participants in the different HR categories during high intensity functional interval training (Fig. 5).
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Percentage of Ɵme (%)
Fig. 5. High intensity interval functional training program.
Exercise Intensity (%HRmax)
Fig. 6. Percentage of time spent by participants in the different heart rate (HR) categories during high intensity functional interval training.
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Traditional Training. In these training program, the CG performed a routine exercise that is usually carried out in their training program (shown on Table 2). Table 2. Traditional training program Days Monday Tuesday
Training program Shuttle drill (40 min), Netting (20 min), Defensive (20 min), Game (40 min) 6 Corner shuttle agility (40 min), Half match court (20 min), Game control, Double match box (40 min) Thursday Shuttle match shuttle double (1 h), Shuttle match smash (40 min), Tappins shuttle match (20 min) Sunday Training at GYM *Extra hours; Sprinting – 5 Reps 6 sets, Push ups – 100, Sit ups – 100
2.4
Statistical Analysis
Data are reported as mean + SD. Repeated measures Mixed analysis of variance (ANOVA) to determine if any change in the dependent variables was a result of the interaction between the type of training program (high intensity functional interval training and traditional training; between subject factors). Dependent variables were measured at three time points (pretest – T1, post 5 weeks – T2, post 10 weeks – T3); which represented the three groups of within subject factors. To allow a better interpretation of the result, effect sizes (ES) were also calculated by using Cohen protocol (1969). Rhea [18] suggested a modified scale for the ES values of 1.0 were considered large [18]. The calculations of the percentage of increase in performance were also calculated. The calculation of the percentage of increase in performance was done by dividing the difference in performance with the performance of the earlier time point and multiplying by 100 [18]. The statistical software package “SPSS Statistics 23.0” was used for statistical analysis. Statistical significance was set at p < 0.05.
3 Results The comparison of aerobic, agility and sprint performance between the control group and experiment group at T2, and T3 was shown in Table 3. Meanwhile, the mean values and standard deviation (Mean + SD) of all measurements were presented in Table 4. At baseline, there were no significant differences in aerobic, agility and sprint between groups. There was a statistically significant different in aerobic fitness between EG and CG, F(1,14) = 4.663, p = .049. The ES between EG and CG in aerobic fitness was large effect size at both, T2 (ES = 1.361, p = .023) and T3 (ES = 2.315, p = .001). Moreover, there was a statistically significant different in agility performance between EG and CG, F(1,14) = 5.443, p = .035, produced a large effect size at T2 (ES = −2.25, p = . 000) and T3 (ES = −2.72, p = .000). However, there was no significant different in sprint performance between groups, F(1,14) = .351, p = .563. The ES between the
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control group and experimental group in the performance of the sprint was trivial at small at T2 (ES = −.375, p = .371) and trivial at T3 (ES = −.143, p = .763). Table 3. Comparison of aerobic, agility and sprint performance between the control group and experiment group at T2, and T3. Variables _ 2max VO (ml/kg/min) Agility (s) Sprint (s)
Time point df F Sig Effect size T1 (1,14) 6.517 .023 1.361 T2 (1,14) 18.354 .001 2.315 T1 (1,14) 25.370 .000 −2.25 T2 (1,14) 47.934 .000 −2.72 T1 (1,14) .855 .371 −.375 T2 (1,14) .095 .763 −.143
Table 4. Comparison of aerobic, agility and sprint performance of the participants at T1, T2, and T3. Variables
Group
Mean (SD) T2
T1 _ 2max Control VO (ml/kg/min) Experiment Agility (s) Control Experiment Sprint (s) Control Experiment
37.9 37.5 33.5 34.1 4.6 4.5
(4.9) (5.8) (2.2) (2.2) (.19) (.4)
34.7 41.1 33.3 31.3 4.4 4.3
T3 (4.7) (5.3) (.66) (.66) (.26) (.15)
35.9 45.8 31.9 29.5 4.2 4.3
(4.3) (5.0) (.87) (.42) (.23) (.19)
%D T2 − T1 (ES)
%D T3 − T2 (ES)
%D T3 − T1 (ES)
−8.48 9.71 −0.51 −8.13 −4.28 −4.07
3.39 (.25) 11.38 (.88) −4.30 (−1.7) −5.95 (−2.81) −4.4 (−.762) −1.52 (−.45)
−5.38 (−.42) 22.18 (1.43) −4.79 (−.72) −13.6 (−2.11) −8.49 (−2.06) −5.53 (−.62)
(−.66) (.63) (−.08) (−1.26) (−1.04) (−.46)
4 Discussions The purpose of this study was to examine the effects of a high intensity interval functional training program on aerobic fitness, agility and sprint. The results showed that there were differences between groups in aerobic fitness and agility. However, no differences between groups were found for sprinting performance. 4.1
Effect of High Intensity Interval Functional Training on Aerobic Fitness
_ 2max in the EG after training 5 In this study there had been increases of performance VO weeks (9.7%) and it further increased after 10 weeks of training (22.2%) while the CG showed no significant improvement after 10 weeks of training. The significant improvement in EG was consistent with Wee et al. [19] and Sperlich et al. [7] finding in which the effects of high intensity interval training usually demonstrated increases of _ 2max by 4.2–13.4%. VO _ 2max point of view, improving aspects of cardiovascular For the improved VO parameters such as heart size, blood flow capacity, and arterial distenibility [20], thus
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increasing the capacity of the cardiovascular system to transport oxygen and resulting _ 2max might be affected by the central _ 2max [20]. This increasing of VO an increase in VO nervous system and peripheral adaptation [19]. Apart from that, the duration and repetition of high intensity interval functional training is enough to improve the level of aerobic fitness among young badminton players. Training intensity at 90–95 HRmax and 3-min active recovery were enough to improve aerobic fitness [21]. Helgerud et al. (2001) completed 4-min intervals at 90–95% maximal heart rate among youth soccer _ 2max of 11%, players over an 8-weeks training period and promoted an increase in VO −1 −1 equivalent to an increased from 37.5 + 5.8 to 45.8 + 5 ml. min kg . 4.2
Effect of High Intensity Interval Functional Training on Agility
This investigation reported significant improvement of 8.1% and 13.6% of agility in EG after training intervention 5 weeks and 10 weeks, respectively. Our result was consistent with those studies using HIIT protocols in badminton, with approximately 3.23% after 4 weeks of training [19]. The significant result in EG, might due to the movement in the high intensity interval functional training was similar to the movement in the four corner agility test. In this study, the HIIT protocol was including the movement of change of direction that was responded to the visual and sound stimuli. The concept of accurate movements, performance towards the accelerations, and decelerations towards the shuttlecock and also backpedaling consisted of the movement of COD [19]. The combination of HIIT protocol with element change of direction gave high pressure to players and might be contributing to the increase in agility performance [17]. Components of agility are an acquired motor skill that can be practiced and badminton players could enhance agility through technical training, pattern running and reactive training [22]. The enhanced motor unit recruitment patterns were a result of improvements in agility [23, 24]. In consequence of training, there is neural adaptations occurred among athletes. These adaptations consequently enhanced the coordination between CNS signal and proprioceptive feedback in athletes [25]. This showed that the sports specific training in racket games contributed to the improvement in agility. 4.3
Effect of High Intensity Interval Functional Training on Sprint
This study showed that there were no significant between groups on sprint performance. This investigation reported less significant improvement after training intervention 5 to 10 weeks respectively were 4.07% and 5.53%. No effect of training HIIT protocols post change was found in 20-m sprint time. Our result was aligned with those Ferrari-Bravo et al. [26] and Fernandez-Fernandez et al. [27], who found a lack of improvement in jumping or strength leg muscle. The skill-related fitness components such as speed and agility are independent locomotor skills and relatively unconnected to each other [27]. Training program in this study was not affected with linear speed. This would guide to the assumption that the training methods of agility and linear speed produce limited transfer to the other directional running modes and suggested to improve muscular power and short linear sprint ability, to use a different combination of training methods [27].
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5 Conclusion In conclusion, high intensity functional interval training for 10-weeks increased aerobic fitness level and agility. Aerobic exercise 3 times per week, 2 sets (5 reps 180 s at _ 2max . Thus 80–95% HRmax; 3-min rest between reps) was effective at improving VO training duration, frequency and intensity in this study were enough to improve aerobic fitness level of the participants. According to ACSM (2000), by training aerobic exercise 3 to 5 times per week for 20–60 min per session, and maintain training _ 2max [28]. A sport such as badminton intensity at 65–90% HRmax would improve VO requires intermittent high-intensity efforts and high loading demands at aerobic systems and anaerobic systems during badminton play and recovery. Hence, aerobic exercises in badminton training could be included to enhance competition during match. Acknowledgements. The research team would like to express their deepest gratitude to the Ministry of Higher Education (MoHe) for funding this project under Prototype Development Research Grant Scheme (PRGS), grant No. PRGS0004-SKK-1-2015.
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13. Léger, L.A., Mercier, D., Gadoury, C., Lambert, J.: The multistage 20 metre shuttle run test for aerobic fitness. J. Sports Sci. 6, 93–101 (1988) 14. Matsuzaka, A., Takahashi, Y., Yamazoe, M., Kumakura, N., Ikeda, A., Wilk, B., Bar-Or, O.: Validity of the multistage 20-m shuttle-run test for Japanese children, adolescents, and adults. Pediatr. Exerc. Sci. 16, 113–125 (2004) 15. Ramsbottom, R., Brewer, J., Williams, C.: A progressive shuttle run test to estimate maximal oxygen uptake. Br. J. Sports Med. 22(4), 141–144 (1988) 16. Ooi, C.H., Tan, A., Ahmad, A., Kwong, K.W., Sompong, R., Ghazali, K.A.M., Liew, S.L., Chai, W.J., Thompson, M.W.: Physiological characteristics of elite and sub-elite badminton players. J. Sports Sci. 27(4), 1591–1599 (2009) 17. Dellal, A., Keller, D., Carling, C., Chaouachi, A., Wong, D.P., Chamari, K.: Physiologic effects of directional changes in intermittent exercise in soccer players. J. Strength Cond. Res. 24(12), 3219–3226 (2010) 18. Rhea, M.R.: Determining the magnitude of treatment effects in strength training research through the use of the effect size. J. Strength Cond. Res. 18, 918–920 (2004) 19. Wee, H.E., Low, J.Y., Chan, K.Q., Ler, H.Y.: Effects of high intensity intermittent badminton multi-shuttle feeding training on aerobic and anaerobic capacity, leg strength, qualities and agility. In: Proceedings of the 5th International Congress on Sport Sciences Research and Technology Support. (icSPORTS 2017), pp. 39–47 (2017) 20. Krustrup, P., Hellsten, Y., Bangsbo, J.: Intense interval training enhances human skeletal muscle oxygen uptake in the initial phase of dynamic exercise at high but not at low intensities. J. Physiol. 559(Part 1), 335–345 (2004) 21. Helgerud, J., Hoydal, K., Wang, E., Karlsen, T., Berg, P., Bjerkaas, M., Simonsen, T., _ 2max Helgesen, C., Hjorth, N., Bach, R., Hoff, J.: Aerobic high-intensity intervals improve VO more than moderate training. Med. Sci. Sports Exerc. 39(4), 665–671 (2007) 22. Holmberg, P.M.: Agility training for experienced athletes: a dynamical systems approach. Strength Cond. J. 31(5), 73–78 (2009) 23. Potteiger, J.A., Lockwood, R.H., Haub, M.D., Dolezal, B.A., Alumzaini, K.S., Schroeder, J. M., Zebas, C.J.: Muscle power and fibre characteristics following 8 weeks of plyometric training. J. Strength Cond. Res. 13, 275–279 (1999) 24. Zubac, D., Šimunic, B.: Skeletal muscle contraction time and tone decrease after 8 weeks of plyometric training. J. Strength Cond. Res. 31(6), 1610–1619 (2017) 25. Craig, B.W.: What is the scientific basis of speed and agility? J. Strength Cond. 26(3), 13–14 (2004) 26. Ferrari Bravo, D., Impellizzeri, F.M., Rampinini, E., Castagna, C., Bishop, D., Wisloff, U.: Sprint vs. interval training in football. Int. J. Sports Med. 29(8), 668–674 (2008) 27. Fernandez-Fernandez, J., Zimek, R., Wiewelhove, T., Ferrauti, A.: High-intensity interval training vs. repeated sprint training in tennis. J. Strength Cond. Res. 26(1), 53–62 (2012) 28. American College of Sports Medicine: ACSM’s Guideliness for Exercise Testing and Prescription, 6th edn. Lippincott Williams and Wilkins, Baltimore (2000)
The Effect of Amplitude (Response Complexity) in Choice Reaction Time Mohd Syrinaz Azli1(&) , Mohar Kassim1 , Jorrye Jakiwa1 Siti Azilah Atan1 , and Emmy Hainida Khairul Ikram2
,
1
Defense Fitness Academy, Universiti Pertahanan Nasional Malaysia, Kem Perdana Sg. Besi, 57000 Kuala Lumpur, Malaysia [email protected] 2 Centre of Nutrition and Dietetics, Faculty of Health Sciences, Universiti Teknologi MARA, 42300 Bandar Puncak Alam, Selangor, Malaysia
Abstract. Research has shown that reaction time (RT) increases as a function of elements and amplitude. Hence, this study aimed to investigate how invalid information regarding the numbers of elements and magnitude of movement influenced programming prior to movement initiation and during movement execution in choice RT. Twelve self-declared undergraduate students with righthanded performed a total of 150 trials of aiming movements with pen along the track way on Calcomp III digitizing tablet sample rate 200 Hz. The visual of the cursor displays on the computer monitor positioned straight in front of the participants. The participants were directed to move the cursor as quickly as possible in a continuous manner to the targets indicated by the four possible stimuli (i.e., 1S, 1L, 2S and 2L). Repeated measures ANOVA revealed that RT was quicker in valid than in invalid conditions F = (3,33) = 13.390, p < 0.05. When early invalid information concerning the precue and stimulus was specified, RT and movement time increased as a function of elements and amplitude. These findings indicated that reprogramming occurred prior to movement initiation during RT. However, the time required to reprogrammed movements did not vary as a function of features of the response. Keywords: Reaction time
Movement time Response complexity
1 Introduction Research has demonstrated that when movement complexity is varied in the response and no information is given about the stimulus, reaction time (RT) will be longer as compared to when you knew early information (Khan et al. 2006; 2008a, b; Klapp 2010). Henry and Rogers (1960) showed that RT was directly related to the number of action elements by contrasting RT with a small-complexity movement (finger lift), a middle-complexity movement (single-ball grasp), and excessive-complexity movement (double-strike ball). They attributed that when the response complexity increased in the movement, more time was needed to initiate the movement. Many researchers have tried to investigate the impact of response complexity that influences RT such as the amount of elements, response duration, and movement © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 54–63, 2020. https://doi.org/10.1007/978-981-15-3270-2_6
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accuracy (Khan et al. 2006; 2008a, b; Mottram et al. 2014; Maslovat et al. 2018; 2019). In this regard, they investigated the effect of response complexity and determined its direct effect on simple RT or choice RT. In simple RT, participants could have preprogramed the response early before the execution of the movement. There was one stimulus and one response. For choice RT, preprograming was not possible because no early information was given; therefore, RT depended on the complexity or duration of the response (Khan et al. 2006). Specifically, the participants were not aware of the upcoming stimulus. Previous study used rapid aiming movement to investigate whether the effect of the nature of the response on RT depended on the magnitude of the movements were programmed prior to movement commencement or during movement implementation (i.e. online) (Khan et al. 2006). In simple RT, participants were informed early about the particular response. The participants, however, had no knowledge about the types of response needed in the choice RT. Their study revealed that simple RT was greater than single-element responses for the two-element responses, whereas no impact was seen in the number of elements on the choice RT. Khan et al. (2006) gave an alternate explanation to this responded programming. In simple RT, they could visually monitor the execution as they already knew the required response before the presentation of the stimulus. Nevertheless, it was not possible to load the response buffer before the stimulus in choice RT, as the response was not known until the stimulus presentation. Therefore, it is possible that online programming was a strategy adopted by the participants in order to minimise RT. They programmed the first element but then delayed the other element until there was movement initiation. In another study by Khan et al. (2008a, b), the RT was longer for the two-element response as compared to the singleelement response when the participants knew what response would be needed before the stimulus. They claimed that when the number of elements was known early, a complex pattern of muscle activity was planned for multiple component movement. Therefore, the purpose of this study was to examine how advance information on the numbers of elements and amplitude of movement affected programming before initiation of movement and during execution of movement in choice RT. The participants performed target aiming movement consisting either a single movement to a target or a reversal movement in which they travelled to one target and then reversed the direction to stop at a second target (Khan et al. 2006). The experiment varied the required amplitude of the target movement and a single-element precue (e.g. 1L and 1S) existed prior to the precue. Prior to the stimulus, the participants were given randomised stimuli in both experiments either valid stimulus or invalid stimulus (e.g. 1L, 1S, 2L, and 2S). The aim of the experiment was to examine whether RT increased when invalid stimulus was present prior to valid response precue and whether reprogramming occurred prior to response initiation or during response execution.
2 Method 2.1
Participants
The selected participants were of 12 self-declared undergraduate students with righthanded of both sexes (male and female), with normal or corrected to normal vision, and
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about 18–30 years of age. Upon participating, they gave their informed consent and the test were performed for research involving human subjects according to the university ethics committee. 2.2
Apparatus
The participants were sitting with their right hand holding a pen and moving horizontally in front of them on a size of 1330 mm 915 mm and sample rate of 200 Hz, Calcomp III digitising tablet (see Fig. 1). The pen movement were made along the path that limited the movement of left and right. The pen tip was fitted in the pathway that prevented movement forward and backward. The pen positioning was represented by a round cursor (4 mm in diameter with a dot of 1 mm wide in the middle) on a 37 inch Mitsubishi Diamond Pro computer monitor 400 mm in front of the participants and 300 mm from the tablet surface. On the monitor screen, a visual display of the starting position, target lines, and the cursor representing the pen position. The starting position was on the left of the screen and consisted of a vertical line of 0.4 cm wide and 4 cm long. There was a rectangle box of 20 mm 15 mm slightly above the starting position where the stimulus appeared. The 1 mm wide and 40 mm long vertical goal lines were situated at 2 cm, 4 cm, and 8 cm to the right of the starting position. During the test, the arm of the participants was covered by an opaque shield.
Fig. 1. Aiming movement that used in the study. The figure shows how the right hand holding a pen on a Calcomp III digitizing tablet with Mitsubishi Diamond Pro computer monitor positioned in front of the subject.
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The starting position, target lines, and the cursor representing the position of the limb appeared on the computer monitor for the beginning of each trial and the participants were needed to move the cursor to the start position (Khan et al. 2008a, b). Once the cursor was correctly aligned, a precue consisting of a mixture of numbers and letters was displayed for 2000 ms in the stimulus display box, and then the precue (1000 ms) was shown, an audio tone signalling the beginning of the of the variable fore period (1500–2500 ms) (Khan et al. 2008a, b). 2.3
Task and Procedure
Participants were instructed to move the cursor as fast and as accurately as possible in a continuous manner to the targets indicated by the stimulus (see Fig. 2) (Khan et al. 2008a, b). Throughout the trials, the stimulus remained visible. Four probable stimuli were present in this test: 1S, 2S, 1L, and 2L (Khan et al. 2008a, b). “1S” was a single element response that allowed the participants to move the cursor to the target line of 4 cm. “2S” was a two-element response that allowed the participants to travel to the 4 cm line and then back to the 2 cm line (Khan et al. 2008a, b). The participants had to move to the 8 cm for the “1L” stimulus, while they had to move to the 8 cm line and reverse back their movement on the 4 cm line (Khan et al. 2008a, b).
Fig. 2. Stimulus diagram display on the screen, starting position and targets at distances of 2, 4 and 8 cm from the start position (adapted from Khan et al. 2008a, b).
The precues or possible stimuli was varied in term of the quantity of input they received about the reaction needed to take. This information might be valid or invalid because in choice RT, they still need to prepare for other possible stimuli. In this experiment, the precue would be a single-element response (i.e. 1L, 1S); however, the
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stimulus might be the same as the precue or randomised. Hence, the participants knew early the precue of the required movement, but did not know which stimulus would be required and needed to prepare any possible stimulus responses. This condition is a bit similar to choice RT in previous research (Khan et al. 2006; 2008a, b); however, the only differences are the precue was given, the stimulus was randomised, and preprogramming was still not possible. The participants performed a total of 150 trials for each precue in the experiment with 120 valid precues (80%) and 30 invalid precues (20%) and the four stimuli occurred in a random sequence. To track the output of the participants at the end of each test, a display of the pen’s trajectory against time was shown on the computer screen of the experimenter regarding their RT milliseconds (ms) and constant error millimetres (mm) in numerical for at each target. The participants would receive feedback and explanation about their error that was calculated from the centre of the target. Overshot target indicated the positive error while undershot target considered a negative error. All the trials in which the participants made the wrong movement (i.e., incorrect number of element or amplitude) or in which the RTs were less than 100 ms or greater than 700 ms were rejected and replicated in the series trails, which amounted to less than 5% of the trials (Khan et al. 2008a, b). The dependent variables measures were consisted of reaction time (RT) and movement time to the first target (MT1) for statistical analysis. RT and MT1 were analysed in this experiment by using two precue conditions (1L and 1S) four responses (1S, 1L, 2S, 2L) repeated measures ANOVAs. All post-hoc analyses were performed by using Tukey’s Honest Significant Difference (HSD) (p < .05) tests.
3 Results 3.1
Reaction Time (RT)
The means of all dependent variables are reported in Table 1. The statistical analysis on RT revealed a significant main effect for response, F (3, 33) = 5.507, p < 0.05. The Tukey post-hoc test was calculated by hand and it showed that the number of elements and amplitude in a response had an effect on RT. As expected, RTs were shortest for the valid conditions and longest for the invalid conditions. Table 1. Means of reaction time (RT), movement time to the first target (MT1) as a function of precue condition, number of elements and movement amplitude. Precue Stimulus
1L 1L
1S
2L
2S
1S 1L
1S
2L
2S
RT (ms) 354.808 414.975 407.865 411.365 404.424 350.173 421.194 404.112 MT1 (ms) 290.9205 246.3059 293.5286 243.9986 306.8904 241.8904 297.6312 245.7032
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An analysis of RT revealed that there was a significant interaction between precue and response, F = (3,33) = 13.390, p < 0.05. In the 1L precue condition, IL valid response differed from the 1S, 2S, and 2L invalid response conditions. Similarly, in the 1S precue condition, 1S valid response differed from the 1L, 2S, and 2L invalid response conditions (see Fig. 3). This showed that amplitude had an effect on RT.
Fig. 3. Comparison mean of RT (ms) and the error bar display standard deviation.
3.2
Movement Time to the First Target (MT1)
The analysis of movement time to the first target (MT1) revealed a significant main effect for response, F (3, 33) = 57.269, p < 0.05. The Tukey post-hoc test was calculated by hand and it showed that for valid precue and responses, the movement time to the first target was shortest for the short amplitude (i.e. 1S, 2S). However, the test also found the two-target advantage but only in certain precues and response conditions. Interestingly, for the 1L precue condition, the two-target advantage was found at 1S and 2S responses. While for the 1S precue condition, the two-target advantage was found at 1L and 2L responses (see Fig. 4). MT1 also revealed that there was a significant interaction for precue and response, F (3, 33) = 3.247, p < 0.05.
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Fig. 4. Comparison mean of movement time to the first target (ms) and the error bar display standard deviation.
4 Discussion Previous study showed that RT response will be longer if participants knew the stimulus presentation beforehand and the complexity of movement varied (Khan et al. 2006; 2008a, b; Maslovat et al. 2018). The one-target movement time advantage is the phenomenon where the RT increases and when the movement execution needs to stop at a single target as compared to when it must move to hit a second target (Lawrence et al. 2016). In the two-target movement time advantage, the RT increases when the movement execution needs to stop and reverses to the opposite direction as the first movement as compared to when it must stop at the first target (Khan et al. 2008a, b). This two-target advantage leads to the dual function of the antagonist muscle activity. According to Maslovat et al. (2018) there is a functional link between muscular forces for a movement that consists of a sequencing and reversal direction of movement. Furthermore, during the movement execution, the antagonist of the muscle on the first element serves as the agonist on the second element and movement times to the first target are quicker as compared to the single-element response (Maslovat et al. 2016; 2018). The purpose of this study was to investigate how invalid information concerning the numbers of element and movement amplitude influenced programming before the start of movement and during the execution of the movement in choice RT. In the valid precue condition, the participants were given the single-element precue and were told to react for the same stimulus for the response (i.e. 1S precue = 1S stimulus or 1L precue = 1L stimulus). For the invalid precue condition, the participants were given the single-element precue, but were told to react to the other presented stimuli if a different
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response occurred (i.e. 1S precue = 1L, 2S, 2L stimulus or 1L precue = 1S, 2S, 2L stimulus). It was hypothesised that when valid precue and valid stimulus were present, the RT would be quicker, whereas a longer RT was required for the invalid precue condition. Based on the current findings, as expected in a valid condition where the participants knew early about the precue and the stimulus (i.e. 1S and 1L), the RT was quicker than in invalid conditions. The present study replicated the previous findings of on RT (Khan et al. 2006; 2008a, b; Maslovat et al. 2018). In this study, it was expected that the number of elements would have an effect and also increase the RT; however, this was not the case. These findings implied that during the movement responses, there was a possibility of online programming occurring during movement execution. In order to slow down the RT, participants might adopt a strategy by only preparing the first element during RT and then monitoring or online programming the second element (Khan et al. 2006; Maslovat et al. 2019). During response initiation, in the twoelement response, the pattern of muscle activity might differ from the one-element response because of the movement complexity. This would lead to changes on all organisations of the muscle activity. Khan et al. (2006) proposed that the organisation of the reversal movement as a single unit of action involved specifying the general pattern of muscle activity prior to response initiation. The present study extended the results of manual aiming movement. It seemed that the RT result had no differing effect in changes of the amplitude. Hence, when there were changes of the element in the response, there would also be changes on RT. It was hypothesised that the two-target movement time advantage would occur in the response; unfortunately, it did not. When comparing the multiple-element responses with single-element movement responses, the movement time to the first target was longer (Lawrence et al. 2016). In addition, it appeared that, when online programming was adopted, the effect of response difficulty on RT would be reduced as fewer elements were programmed during the RT interval. Khan et al. (2008a, b) reported that the two-target movement time advantage for reversal movement direction was quicker for the dual-element rather than for the single-element response. Moreover, they stated that the two-target reversal movements were organised as single unit of action prior to response initiation. In this study, the participants used a manipulandum where they placed their forearm on the padded shaft and used the elbow joint as the function of the movement response. However, in the present study, the two-target movement time advantage did not appear when the participants needed to slide a pen on a digital tablet. It could be suggested that the two-target movement time advantage could be found in the elbow function movement, not with the pen-sliding function movement. Moreover, during the movement response in the elbow and pen-sliding function movements, anatomical factors such as muscle involved, joint in use or body position might be the effects that slowed down the RT and movement time. For example, in the present experiment, the movement of sliding a pen involved the movement of the shoulder and elbow joint, whereas in a previous experiment by Khan et al. (2008a, b), the movement only involved a single-plane motion, which was only the elbow joint. Hence, the twotarget advantage did not emerge because of the anatomical factor (Mohagheghi and Anson 2002) and the integration between muscular forces acting on both elements (Lawrence et al. 2016).
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In a previous study, Klapp (2010) reported an association between the amplitude of movement and the diameter of the target. When the target’s diameter was small, the RT reduced with the increase in the movement’s length. In the present study, the error to the first target showed that the participants were inclined to make a large error for the large amplitude. When it came to the smaller amplitude, the error to the first target was decreased and for short amplitude movements the participants needed to increase their accuracy and control the demand for the smaller target, hence, an increase in preparation time. They also revealed that more time was needed to prepare for the execution of shorter amplitudes.
5 Conclusion The results of this study discovered that RT increased as a function of components or elements and amplitude in the response. It has been suggested that the RT was increased due to the fact that the participants reprogrammed the movement features before movement initiation because two stimulus features changed. However, the time required to reprogrammed the response did not vary. Henry and Rogers (1960) reported that the RT was greater as a function of the movement complexity and this was due to the increase in programming before response initiation. In the present study, it is important to understand the kinematic data such as the time to peak velocity because it represents the features of the movement, hence the changes of number parameter are investigated.
References Henry, F.M., Rogers, D.E.: Increased response latency for complicated movements and a “memory drum” theory of neuromotor reaction. Res. Q. 31, 448–458 (1960) Khan, M.A., Lawrence, G.P., Buckolz, E., Franks, I.M.: Programming strategies for rapid aiming movements under simple and choice reaction time conditions. Q. J. Exp. Psychol. 59, 524– 542 (2006) Khan, M.A., Mourton, S., Buckolz, E., Franks, I.M.: The influence of advance information on the response complexity effect in manual aiming movements. Acta Psychol. 127, 154–162 (2008a) Khan, M.A., Tremblay, L., Cheng, D.T., Luis, M., Mourton, S.J.: The preparation and control of reversal movement as a single unit of action. Exp. Brain Res. 187, 33–40 (2008b) Klapp, S.T.: Comments on the classic Henry and Rogers (1960) paper on its 50th anniversary: resolving the issue of simple versus choice reaction time. Res. Q. Exerc. Sport 81(1), 108–112 (2010) Lawrence, G.P., Khan, M.A., Mottram, T.M., Adam, J.J., Buckolz, E.: The integration of sequential aiming movements: switching hand and direction at the first target. Acta Psychol. 164, 181–187 (2016) Maslovat, D., Chua, R., Klapp, S.T., Franks, I.M.: Independent planning of timing and sequencing for complex movements. J. Exp. Psychol. Hum. Percept. Perform. 42(8), 1158 (2016)
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Maslovat, D., Chua, R., Klapp, S.T., Franks, I.M.: Preparation of timing structure involves two independent sub-processes. Psychol. Res. 82(5), 981–996 (2018) Maslovat, D., Klapp, S.T., Forgaard, C.J., Chua, R., Franks, I.M.: The effect of response complexity on simple reaction time occurs even with a highly predictable imperative stimulus. Neurosci. Lett. 704, 62–66 (2019) Mohagheghi, A.A., Anson, J.G.: Amplitude and target diameter in motor programming of discrete, rapid aimed movements: Fitts and Peterson (1964) and Klapp (1975) revisited. Acta Psychol. 109, 113–136 (2002) Mottram, T.M., Khan, M.A., Lawrence, G.P., Adam, J.J., Buckolz, E.: Sequential aiming with one and two limbs: effects of target size. Acta Psychol. 151, 83–88 (2014)
Effect of Medial Longitudinal Arch Height on Static and Dynamic Balance Among UiTM Female Athletes Salvastore Sam and Nur Khairunisa Abu Talip(&) Universiti Teknologi MARA, Sarawak Branch, Kota Samarahan, Malaysia [email protected], [email protected]
Abstract. The purpose of this study were to identify the effect of medial longitudinal arch (MLA) height on static and dynamic balance among female athletes. The participants of this study were the active female athletes from Universiti Teknologi MARA (UiTM), Samarahan Branch. The participants were divided into three groups according to their foot arch which include low (n = 30), normal (n = 30) and high (n = 30) arch height. The foot arch or structure was measured by using the wet test (WT). The stork stand test (SST) was used to assess participant static balance (SB), while the balance beam speed test (BBST) was used to assess participant dynamic balance (DB). Significant level was set at p < .05. The result showed that there was a significant difference between groups on SB (p = .041) and DB (p = .0001) test. There was also a significant difference (p = .014) between SB and DB for high arch group. There was no significant difference between SB and DB on low arch (p = .153) and normal arch (p = 1.00). Thus, the MLA height have effect on static and dynamic balance. Keywords: Medial longitudinal arch height arch Static balance Dynamic balance
Low arch Normal arch High
1 Introduction Foot is a complex structure that capable to absorb shock. Human foot experiences many structural changes (Shahrivar et al. 2014). During weight bearing activities or any type of sports, the foot arch plays a crucial role in absorbing ground reaction forces generated and supporting body weight (Zhao et al. 2017). The structure of the foot arch and the biomechanics of the lower leg are closely related (Sivachandiran and Kumar 2016). One of the most important structural properties of foot is the medial longitudinal arch (MLA) height (Shahrivar et al. 2014). According to Zhao et al. (2017), MLA height can be categorized high arch (HA), normal arch (NA) and low arch (LA). Kelikian and Sarrafian (2011) stated that the most common types of foot include normal, pronated and supinated foot. Lacking on foot mobility may diminish the ability of the lower leg to function optimally during the weight bearing exercises or activities, thus limiting movement and affect the other parts of the lower leg. Apart from that, it is also known that MLA height is the source of many differences and any relationship © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 64–70, 2020. https://doi.org/10.1007/978-981-15-3270-2_7
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between the lower limb injuries and MLA result in some studies are still ended with controversial results (Nakhaee et al. 2008). Overweight, geographic which is the physical features of an area or surface and cultural factors such as how to wear shoes are believed to be the factors to flat foot. In daily activities, balance is one of the inseparable components and the maintenance of the stature control is important (Hakimipour and Fadaee 2015). Balance define as the process of maintaining the centre of the body at the dependence level as well as to control of the body position to indicate the sustainability and the direction (Shumway-Cook et al. 2000). Balance required the centre of the central and peripheral components of the nervous system to interact continuously (Hertel et al. 2002). It is the ability to control and maintain the centre of gravity of the body at certain rate or level. Balance can be measured as SB and DB. Cote et al. (2005) stated that the SB refers to the ability to maintain the body’s centre of gravity at the dependence level. Meanwhile, DB is the ability of the body to maintain the constant dependence level while doing a movement. In motor fitness, balance is considered as one of the main components and the fundamental factors in maintaining the physical posture in daily activities. Maki et al. (2008) claimed that individual with less balance has a higher risk to injury. MLA height impact on physical performance is still unclear. Mousavi (2011) investigated the relationship of MLA height between SB and DB on male students and concluded that MLA height has some significant relationship with DB performance. Tsai et al. (2006) which conducted a study on 45 young adults to investigate the impact of different foot structure on static standing postural control concluded that individuals with pronated feet or supinated feet have poorer postural control than individuals with neutral feet. Therefore, the present study recruited UiTM Sarawak Branch athletes. As the physical performance is also integrated consequence of multiple body systems (Zhao et al. 2017), it is still unknown whether the arches of the foot may affect a physical performance of an athlete Zhao et al. (2017) that studied MLA height and balance on adult men proposed that there is a need for the future research conduct focusing on women.
2 Methods 2.1
Participants
A total of 90 (n = 90) female athletes was involved in this study. Each group consists of 30 participants. The participants were divided into three groups according to the foot arch which is LA, NA and HA. According to Greenwood and Sandomire (1950), 30 samples for every-each group will represent the population and this was supported by previous studies by Ashkezari (2014), and Hakimipour and Fadaee (2015). The range age of the participants was between 21 to 23 years old. All the participants in the present study must be healthy and free from any injuries, currently active in sports and have the experience of representing the university in any kind of competition in the current year such as Sukan Institusi Pendidikan Tinggi (SUKIPT), Karnival Sukan Mahasiswa UiTM (KARISMA) or Majlis Sukan Universiti Malaysia (MASUM).
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Instrumentation
The researcher distributed PAR-Q form, International Physical Activity Questionnaire (IPAQ) form and consent form which required to be answered and agreed by the participants. Next, the researcher used WT to identify participants’ types of foot and divided them into three groups (HA, NA, or LA) according to the MLA height. The SBT was used to measure SB, while the BBST used to measure participants’ DB. 2.3
Procedures
The researcher explained about the study to the participants, all questions been answered clearly. All participants cleared to participate in the study by passing the PAR-Q form (ACSM 2014). Next, the IPAQ (Thuy et al. 2010) was used to assess the participant’s activity level as requirement to determine whether the participants met the criteria of the present study. It was used to assess the participant’s health related physical activity. Next, the participants performed WT to identify participant’s types of foot arch (Rasheed and Pagare 2015). In this study, the researcher used black ink to measure foot print on a piece of paper. The SBT was used to measure SB (Tabrizi et al. 2013), in which the participants stood on one leg (dominant leg) as long as possible with the eye closed. Time taken recorded in seconds (s) and converted according to 0 to 5 scale rating; longer time perceived as better SB. 0 indicated poor SB while 5 indicated a greater SB. The BBST was used to measure participant’s DB (Tsigilis et al. 2001), in which participants were asked to walk along a straight beam as fast as they can. The result was referred to the norm of 0 to 5 scale, with 0 indicated poor DB while 5 indicated a greater DB (Tsigilis et al. 2001).
3 Results Table 1 presented the mean (M), standard deviation (SD) of SB and DB test based on types of foot arch (Fig. 1). Table 1. Mean, standard deviation of SB and DB test for LA, NA and HA Foot arch SB Low arch Normal arch High arch DB Low arch Normal arch High arch
M 4.600 4.533 4.067 4.300 4.533 3.567
SD .814 .860 .94 .837 .507 .858
n 30 30 30 30 30 30
Effect of Medial Longitudinal Arch Height on Static and Dynamic Balance
5 4.5 4
4.6 4.3
4.533 4.533
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4.067 3.567
3.5 3
SB
2.5
DB
2 1.5 1 0.5 0
LA
NA
HA
Fig. 1. Figure showed the comparison of mean for SB and DB test for LA, NA and HA groups.
Tables 2 and 3 shown that there was a significant difference on SB (p = .041) and DB (p = .0001) between LA, NA and HA groups. Table 2. ANOVA test for SB between LA, NA and HA Variable Sum of squares df Mean square F Sig. Between groups 5.067 2 2.533 3.313 .041* Within groups 66.533 87 .765 Total 71.600 89 Table 3. ANOVA test for DB between LA, NA and HA Variable Between groups Within groups Total
Sum of squares df Mean square F Sig. 15.267 2 7.633 13.516 .0001* 49.133 87 .565 54.400 89
Meanwhile, Tukey post hoc test in Table 4 was conducted to measure the point of differences between groups (foot arch) in SB as well as in DB group. Table 4. Tukey post hoc test results comparing SB and DB between groups Balance test MLA height MLA height p-value SB NA LA .95 HA .10 LA HA .05* DB NA LA .455 HA .0001* LA HA .001*
Sig. Not significant Not significant Significant Not significant Significant Significant
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Table 5 presented the relationship between SB and DB in different MLA heights (LA, NA and HA). There were no significant differences between SB and DB in LA (p = .153) and NA (p = 1.00). However, there was a significant difference between SB and DB in HA group (p = .014). Table 5. Comparison between SB and DB within types of arch (LA, NA and HA) MLA height p-value Low arch .153 Normal arch 1.00 High arch .014*
4 Discussion The current study has found out there was a significant difference (p = .041) on SB between LA, NA and HA groups. The results are similar to the study that has been conducted by Hakimipour and Fadaee (2015) stated that LA has a better SB than the HA. LA is considered to have a flexible feet and greater ability to absorb ground reaction forces which it could influence the SB of a person (Zhao et al. 2017). This indicated that LA has a better SB than the HA, but not significantly better than NA. LA have better SB compare to the other two type of foot is because LA have a larger base of support. The foot cover almost the whole surface of the foot therefore LA is more stable. NA and HA has smaller base of support compare to the LA which may affect the SB. In order to improve the SB for NA and HA, female athletes should focus more on the strength training or muscular activity to help strengthen the lower extremities especially the foot structure to improve the SB. Tsai et al. (2006) on the other hand, stated that individuals with pronated feet or supinated feet have poorer postural control than individuals with neutral feet. The current study also found out there was a significant difference (p = .0001) on DB between LA, NA and HA groups. NA and LA groups scored significantly better DB test as compared to HA. Zhao et al. (2015) found out that HA was negatively associated with ankle muscle strength. This means that it will affect the physical performance especially on the DB. It is also reported that HA is linked to lower extremity bone injuries and stress fracture, ankle injuries and foot pain (Williams and McClay 2000; Burns et al. 2005). The foot arch ankle muscle strength plays an important role in supporting arch structure in order to enhance dynamic movement. Foot plays an important role in DB. Pronated foot may lead to HA, provide a bad support in absorbing ground forces during activities or sports which also can affect the DB because person with HA have a higher risk of more foot pain (Burns et al. 2005). The result showed there was no significant different (p = .153) on LA between SB and DB among UiTM female athletes. Therefore, LA able to maintain their balance in both SB and DB test, but best at SB due to a greater base of support provided in LA. In the present study, LA reported best in SB amongst the three groups. LA has spring ligament and tendon of tibialis posterior muscle are stretched and lost the function of MLA (Sivachandiran and Kumar 2016).
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The current study has also found out there was no significant difference (p = 1.00) between on SB and DB in NA among UiTM female athletes. This is because the NA provided a more elastic and springy connection between the forefoot and hind foot (Hakimipour and Fadaee 2015) this provides the same support for SB and DB, which creates lower level of muscle stress applied on the foot during movement as compared HA. SB and DB are influenced by the ability or capability of a person’s foot to withstand the pressure applied during movement. The present study also examined there is a significant difference (p = .014) of HA between SB and DB. Lack of supportive base made the DB test significantly harder than SB test. HA has the smallest base of support which makes it the most unstable balance. In overall foot types, HA in particular shown poor SB and DB as compared to LA and NA, due to the abnormal distribution pattern on the foot that increase the risk of injuries. Moreover, Zhao et al. (2017) found out that individual that have HA has significantly lower ankle muscle strength. Thus, this could explain the DB is scored significantly lower balance than SB. Common report also stated LA and HA has more injuries including fractures and foot pain (Molgaard et al. 2010).
5 Conclusion The present study concluded that there is a significant effect of MLA height (LA, NA and HA) on SB and DB among UiTM female athletes. There is also a significant difference of HA between SB and DB test. Whereas, there is no significant difference between SB and DB in both LA and NA groups. In overall, the NA group has better SB and DB, while HA showed to have the weakest SB and DB performance. Therefore, this study helps in examining the potential relationship between types of foot and static and dynamic balance.
6 Recommendation It would be recommended for future study may include deeper physiological knowledge about foot structure (MLA height) and the mechanism of balance. Apart from that, various physical performance tests could be included to investigate the effect of MLA height on the physical performance such as speed, agility and power. Future researchers could also investigate and apply a corrective exercise program that may fix or alleviate LA and HA structure. This may require longer period of exercise training and adaptation to be applied to the participant.
References Ashkezari, K.M.H.: The effect of the medial longitudinal arch height of the foot on static and dynamic balance of male college athletes. Master Degree thesis, University of Tehran, Tehran (2014) Burns, J., Crosbie, J., Hunt, A., Ouvrier, R.: The effect of pes cavus on foot pain and plantar pressure. Clin. Biomech. 20(9), 877–882 (2005)
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Cote, K.P., Brunet, M.E., Gansneder II, B.M., Shultz, S.J.: Effects of pronated and supinated foot postures on static and dynamic postural stability. J. Athl. Train. 40(1), 41 (2005) Greenwood, J.A., Sandomire, M.M.: Sample size required for estimating the standard deviation as a percent of its true value. J. Am. Stat. Assoc. 45(250), 257–260 (1950) Hakimipour, M., Fadaee, E.: The effect of the medial longitudinal arch height of the foot on static and dynamic balance of female college athletes. Int. J. Sports Stud. 5(8), 1004–1009 (2015) Hertel, J., Miller, S.J., Denegar, C.R.: Intratester and intertester reliability during the star excursion balance tests. J. Sport. Rehabil. 32(5), 194–201 (2000) Kelikian, A.S., Sarrafian, S.K. (eds.): Sarrafian’s Anatomy of the Foot and Ankle: Descriptive, Topographic. Functional. Lippincott Williams & Wilkins, Philadelphia (2011) Maki, B.E., Cheng, K.C.C., Mansfield, A., Scovil, C.Y., Perry, S.D., Peters, A.L., Fernie, G.R.: Preventing falls in older adults: new interventions to promote more effective change-insupport balance reactions. J. Electromyogr. Kinesiol. 18(2), 243–254 (2008) Molgaard, C., Lundbye-Christensen, S., Simonsen, O.: High prevalence of foot problems in the danish population: a survey causes and associations. Foot (Edinb) 20(1), 7–11 (2010) Mousavi, S.H.: Association of the medial longitudinal arch of the foot with static and dynamic balance in the boys 22 to 25 years old. Sports Med. J. 3(7), 942–953 (2011) Nakhaee, Z., Rahimi, A., Abaee, M., Rezasoltani, A., Kalantari, K.K.: The relationship between the height of the medial longitudinal arch (MLA) and the ankle and knee injuries in professional runners. The Foot 18(2), 84–90 (2008) Rasheed, M.Q.H., Pagare, S.B.: Effect of flat foot deformity on selected physical fitness components in school going children. Int. J. Sci. Res. Publ. (2015) Shahrivar, M.F., Sokhanguei, Y., Behboodi, I.: The effect of insole with corrective exercises on some of physical and motor fitness factors in girls with flat foot. Eur. J. Exp. Biol. 4(1), 534– 537 (2014) Shumway-Cook, A., Brauer, S., Woollacott, M.: Predicting the probability for falls in communitydwelling older adults using the Timed Up & Go Test. Phys. Ther. 80(9), 896–903 (2000) Sitti, S., Koc, H., Cebi, M.: A comparison of static and dynamic balance performance of skiers. World J. Sports Sci. 10(4), 39–43 (2015) Sivachandiran, S., Kumar, D.G.: Effect of corrective exercises programme among athletes with flat feet on foot alignment factors. Int. J. Phys. Educ. Sports Health 3(6), 193–196 (2016) Tabrizi, H.B., Abbasi, A., Sarvestani, H.J.: Comparing the static and dynamic balances and their relationship with the anthropometric characteristics in the athletes of selected sports. MiddleEast J. Sci. Res. 15(2), 216–221 (2013) Thuy, A.B., Blizzard, L., Schmidt, M., Luc, P.H., Magnussen, C., Dwyer, T.: Reliability and validity of the global physical activity questionnaire in Vietnam. J. Phys. Act. Health 7(3), 410–418 (2010) Tsai, L.C., Yu, B., Mercer, V.S., Gross, M.T.: Comparison of different structural foot types for measures of standing postural control. J. Orthop. Sport Phys. Ther. 36(12), 942–953 (2006) Tsigilis, N., Zachopoulou, E., Mavridis, T.: Evaluation of the specificity of selected dynamic balance test. Percept. Mot. Ski. 92, 827–833 (2001) Williams, D.S., McClay, I.S.: Measurements used to characterize the foot and the medial longitudinal arch: reliability and validity. Phys. Ther. 80(9), 864–871 (2000) Zhao, X., Tsujimoto, T., Kim, B., Tanaka, K.: Association of arch height with ankle muscle strength and physical performance in adult men. Biol. Sport 34, 119–126 (2017)
The Relative Age Effect in Malaysia Youth Athletes Shaza Mohd Shah1, Jeffrey Low Fook Lee1, Nursyaidatul Hafiza Madzlan1,2(&), Saidatul Nur Syuhadah Mohamed Sabadri2, and Maisarah Mohd Saleh2 1
2
Sultan Idris Education University, Tanjung Malim, Malaysia [email protected] University Teknologi Mara Cawangan Pahang, Jengka Campus, Bandar Pusat Jengka, Malaysia
Abstract. The over-representation and selection of players born in the early part of a year compared to those born later is called the relative age effect (RAE). Previous studies have shown this phenomenon exist among popular sport such as ice hockey and football. The over representation of relatively older and biologically matured players were assumed due to bigger physique, thus provide more advantage. The aim for this study was initially to determine if a relative age effect present in the sample of athletes competing in MSSM across Malaysia in 2015. The athletes birth date (n = 9,756) athletes participating the 2015 MSSM national level age group (U12, U15, U18) competitions) were obtained from the Director of Sports Department, Ministry of Education Malaysia. The Chi-square goodness of fit test was used to analyze on each age group between female and male and overall data of each age group. The result showed there were an existence of RAE in female and male athletes in each age group and also the present of RAE. There were more players born in the first three months of the year (Jan–Mar) compared to the last three (Oct–Dec). The over representation of early born players is suggested that they may have been selected based on their physical advantage and the selectors may have missed out skillful but physically less advantaged players. Keywords: Relative age effects
MSSM 2015 Selection of players
1 Introduction The relative age effect phenomenon is an issue that has been debated by many sport development researchers. Annual age-grouping is a process used to categorize children into manageable cohorts that are commonly used in sports and education. These annual age-grouping may provide advantages or disadvantages for an individual. In youth sports, the participants are grouped by age which to ensure equals opportunities, however, different physical growth arise due to the significant of maturity (Campo 2010). The differences of the chronological age in the same age group known as relative age and the consequences of it known as the relative age effect (RAE). The © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 71–79, 2020. https://doi.org/10.1007/978-981-15-3270-2_8
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existences of the relative age effect were documented in both educational and sports environment (Bell et al. 1997). The relative age effect (RAE) first discovered when Barnsley et al. (1985), has examined the data from the 1982–83 NHL season and discovered that almost twice players were born in the early of the year 32.0% in January–March) compared to the 1 last quarter (16.2% in October–December). As in Canadian Junior Leagues, the Ontario Hockey League (OHL) and the Western Hockey League (WHL) revealed that, most of the players were born in the early quarter of the year compared to last quarter of the year (Barnsley et al. 1985). Based on the previous research, the RAEs in the education revealed that the children who born in the first quarter of the year has better cognitive achievement and motor skills compared to those who born later of the year. Besides, they have the higher score on standardized reading, math and spelling tests than the children born the last quarter of the year (Sprietsma 2010). Early and later born can results in difference of the size, strength and ability especially at young age. For example, child who turns 5 years old in January will be nearly 20% older compared to a child born in December has their 5th birthday. In most of sports, the early born get noticed by the coaches due to the physical advantages. As the results, early born were prone to be selected in higher level competition (Addona and Yates 2010). The relative age effect refers to the grouping among children in the same chronological age group (Wattie et al. 2015). For example, all children whom born between 1st January to 31st December in 2009 will be eligible to enroll into Year One in the Malaysian schools system in 2016. Another example in Malaysian schools sports, all school children who are born before 1st January 2003 are eligible to participate in the under 12 year’s age group competition for 2016. The occurrence of RAE amongst athlete suggested that most of the athletes born in the early of the year. To ensure and provide fair playing fields for different levels of development, most of sport system categorized athlete according to a chronological age (Baker et al. 2010). Sports league usually arranged according to the chronological age to ensure a fair competition. The chronological age divided from 1st January to 31st December in a year. Thus, this will benefit the people who were born on the early of the year. For example, in Malaysia the cut-off system using 1st January to end of December to group young athletes. The cut-off system may differ according to the country. In order to reduce physical maturation advantages between young athletes, they were separated according into age-group. This allows a fair coaching and evaluation of an athlete (Schorer et al. 2013). The RAE in football both international and youth soccer has been a research topic since 1990s. There are reasons on the preferred selection of the behavior for an immediate glory on long term goal for the promotion of talent. A relative age effect has been a vigorous study. This is because previous study has shown that the number of selections and minutes played vary with relative age in senior soccer. The relative age effect (RAE) in sport shows the higher present of athletes born in the first quarter of the year compared to those born later of the year. Due to the cut off system established in sporting system. The data of European professional football were obtained to identify the presence of RAEs according to their playing position. As the results of the study, RAEs existed in professional football in Italy, France and Spain.
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However, when differentiated by playing position there is a different RAE incidence in the five championships analyzed (Salinero et al. 2013). Contrast with several studies which it was conclude that, there is no difference in the presence of RAEs among playing position in young footballers (Campo 2010). Youth sports competitions frequently built on a specific age group. The sports for youth should be a platform for them to improve their skills, increase their physical ability and the most important is enjoying playing with peers having similar abilities. However, the youth sports like soccer has upgrades from a recreational sport to a more competitive level. When combined with coaches objective on winning in a competition, the selection of the players appear to be in those who born in the early of the years. In order to determine factors of influencing the selection of the player, a number of studies had explored different variables. The coaches may only stress on finding the differences on physical component that may influence the performance. The physical component in football may include endurance, speed, agility, and etc. These physical component being compared between players born early of the year (1st and 2nd quarter) and players born later of the year (3rd and 4th quarter) within an age group. Most of the studies focused on the relative age effect in youth soccer. The focus of the study is to provide a further examination of the RAE pattern across different age (U12, U15 and U18) in developmental competition in Malaysia. Also, this study conducted to determine if there was an overrepresentation of the athlete in the cohort and underrepresentation of the athlete in the cohort.
2 Method 2.1
Research Design
To examine the birth date distribution in this competition, players were divided into four quarters. 1st, 2nd, 3rd, and 4th quarter corresponding to birth dates distribution among the player who represents Majlis Sukan Sekolah Malaysia (MSSM) in 2015. 2.2
Participants
The participants of the study were the athletes who participated in Majlis Sukan Sekolah Malayisa (MSSM) 2015. The athletes competing in the U12, U15 and U18 (N = 9,756) age groups in the MSSM during the year of 2015 used in this study. 2.3
Procedure
The selected participants were going through a selection by stages. The name of the athletes that represents MSSM more than once was not duplicated. In these tournament, U12 athletes compete in 24 type of sport which are aquatic, badminton, track and field, tenpin bowling, cross country, ping pong, rugby, sepak takraw, squash, hockey, volleyball, handball, football, golf, chess, artistic gymnastic, archery, yacht sailing, softball, cricket, tennis, gymrama and netball. For U15, athletes compete in 18 type of sports which are aquatic, badminton, track and field, basketball, tenpin bowling, cross
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country, ping pong, rugby, sepak takraw, squash, football, golf, chess, artistic gymnastic, archery, yacht sailing, tennis and netball. While for U18, athletes compete in 19 types sport which are badminton, track and field, ping pong, rugby, sepak takraw, squash, hockey, volleyball, football, golf, chess, artistic gymnastic, archery, yacht sailing, handball, softball, cricket and tennis. The records data of the player MSSM in 2015 were available in statistic that provided by Sports Department, Ministry of Education. The player birthdates were collected throughout the year where the sports were organized by the MSSM in 2015. All the observed birthday were classified into 4 quarter. The quarters are defined as: 1st quarter = birth dates in: January to March, 2nd quarter = birth dates in: April to June, 3rd quarter = birth sates in: July to September, and 4th quarter = birth dates in: October to December. 2.4
Statistical Analyses
All statistical analyses perform using SPSS (statistical software package 20.0). The data were summarized using routine descriptive statistics. The presence of an RAE was tested using a chi-square goodness of fit (Kirkendall and Donald 2014). All statistical analyses were performed using the SPSS statistical software package. The birth date distributions were tested using chi-square statistics. Statistical significance was tested at the 5% level.
3 Result The birth distributions of athletes were examined between male and female athletes. Based on the results, the significant of chi-square values were found for all age divisions (U12, U15 &U18). A consistent pattern of over-representation in Quartile 1 & 2 and under-representation in Quartile 4 was present. Based on the data collected, for overall U12 athletes competed in 23 sports (Aquatic, Badminton, Track and field, Tenpin Bowling, cross country, ping pong, rugby, sepak takraw, squash, hockey, volleyball, handball, football, golf, chess, artistic gymnastic, archery, yacht sailing, softball, cricket, tennis, gymrama and netball), the overrepresentation of RAE was identified in the early quarter of the year and underrepresentation of RAE in the late quarter of the year. Similar result was found in overall data of the birth distribution in U15 athletes as the overrepresentation of RAE was identified in the early quarter of the year and underrepresentation of RAE in the late quarter of the year in 18 type of sports which are aquatic, badminton, track and field, basketball, tenpin bowling, cross country, ping pong, rugby, sepak takraw, squash, football, golf, chess, artistic gymnastic, archery, yacht sailing, tennis and netball. While for overall data in U18, athletes compete in 19 types sport which are badminton, track and field, ping pong, rugby, sepak takraw, squash, hockey, volleyball, football, golf, chess, artistic gymnastic, archery, yacht sailing, handball, softball, cricket and tennis also point out the overrepresentation in early quarter and underrepresentation in the late quarter of the year (Figs. 1, 2 and 3 and Table 1).
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U12 900
807
800
No. of athletes
700
592
600 463
500
407
398
400
317
300
MALE 270
244
FEMALE
200 100 0 Q1
Q2
Q3
Q4
QuaƟle
Fig. 1. The birth dates distribution of U12 athletes competing in MSSM 2015. The male athletes who born in the 1st quartile (807), 2nd quartile (592), 3rd quartile (398) and 4th quartile (270) while the male athletes who born in the 1st quartile (463), 2nd quartile (407), 3rd quartile (317) and 4th quartile (244).
U15 600
568
No. of athletes
500 400
453 376
368 287
300
262
274
245
200
MALE FEMALE
100 0 Q1
Q2
Q3
Q4
QuaƟle
Fig. 2. The birth dates distribution of U15 athletes competing in MSSM 2015. The male athletes who born in the 1st quartile (568), 2nd quartile (453), 3rd quartile (376) and 4th quartile (274) while the male athletes who born in the 1st quartile (368), 2nd quartile (287), 3rd quartile (262) and 4th quartile (245).
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U18 900
805
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No. of athletes
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645
600 456
500 374
400
MALE
354 300
FEMALE
272
300
219
200 100 0 Q1
Q2
Q3
Q4
QuarƟle
Fig. 3. The birth dates distribution of U18 athletes competing in MSSM 2015. The male athletes who born in the 1st quartile (805), 2nd quartile (645), 3rd quartile (456) and 4th quartile (354) while the male athletes who born in the 1st quartile (374), 2nd quartile (300), 3rd quartile (272) and 4th quartile (219). Table 1. Birth dates distribution of MSSM 2015 athletes. MSSM 2015
No of athletes Birth quarter 1st 2nd 3rd U12 MALE 2067 807 592 398 U12 FEMALE 1431 463 407 317 U15 MALE 1671 568 453 376 U15 FEMALE 1162 368 287 262 U18 MALE 2260 805 645 456 U18 FEMALE 1165 374 300 272
p value 4th 270 244 274 245 354 219
.000 .000 .000 .000 .000 .000
4 Discussion Studies on RAE have grown over the year. The purpose of this study was to determine if the relative age effect was present within a cohort of MSSM 2015 athletes. The overrepresented of athletes born early of the year were recognized. The general birthdates distribution of U12 athletes competing in MSSM 2015 showed that 67.7% of the male athletes were born in early quarter of the year while 32.3% of the male athletes were born the late quarter of the year. Same goes the female athlete the birth distribution show that 60.8% were born in early of the year and 39.2% were born late of the year. As for U15 and U18, the general birth distribution shows that overrepresentation
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of athletes born in the early quarter of year and underrepresentation of athletes born in the late quarter of the year. The main objective of the present study is to examine the presence of RAEs in the MSSM competitions across Malaysia. Thus, the aim for these studies was initially to determine if a relative age effect present in the sample of athletes competing in the MSSM competitions in 2015. The birthdates of the players participating in the under 12/under 15 and under 18 athletes were obtained to determine if skewed birthdate distributions indicated the presence of RAEs. The consequences of RAE phenomenon repeatedly became bias against the late born and the waste of potential talent. However, there has no component identified as the limit factor that leads for the underrepresentation of younger athletes at the highest levels of sport. The existing sport structure had been accepted as the main factors RAEs existing (Cobley et al. 2009). The finding of this study consistent with previous studies where the relative age effect been tested in popular sport such tennis. Based on the findings, RAES were more consistent at higher competitive level. There were 42.1% of players played in national level born the first quarter of the year. Besides that, accordingly, there is no difference found in any maturity, anthropometric and fitness characteristic of the players. Yet, compared with early born, late born players who were selected into elite squads did not differ in maturation, anthropometric and fitness characteristics (Ulbricht et al. 2015). Previously, the birthdates of professional female and male basketball players from 1943–1954 were examined. There were 1,323 males and 405 female basketballs played during the season and categorized players into quartile using 1st August as the cut-off date. No presence of RAE was found among the birth distribution in female. However, there is a significant of RAEs found in professional male basketball players (Abel et al. 2011). In contrast, with our finding which is, there was a significant of RAEs in both female and male athletes participated in MSSM 2015. As in for other countries, the study focuses on the demanding sports. Recent study examined the existence of relative age effect (RAE) in the professional football teams of ten different European countries showed that RAE significance in 2000–2001 seasons in all countries for Portugal and Spain (Helsen et al. 2012). Same finding with the present studies revealed that in all age categories, especially in the U17, U15 and U14 football teams, birth-month distribution in the first month of the year (January) and in the first quarter is significantly higher than in the last month (December) and in the last quarter of the year. Thus, this indicates that, according to the chronological age, players born in the early of the year prone to be in the team (Mulazimoglu 2014). Since, the early born often selected to be in the team, those who born later in the year tends to dropout and loss interest to play. Based on the previous studies conducted among French Male Soccer players in 2006–2007 seasons indicated that, there were significant differences between dropouts and birthmonths distribution. Based on the findings, the distribution of drop out athletes especially in five categories (U9, U11, U13, U15 and U18) present among players who born in the later of the year (Delorme et al. 2010).
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5 Conclusion The present study is the first to show the relative age effect in a championship across Malaysia. Furthermore, the current findings also clearly demonstrated an overrepresentation of players born in the first and second quarters of the selection year. The sporting systems develop in a way of promoting equality and chances for all same age group to succeed in sports. However, the current sporting system produces relative age differences among teammates. As a results, early maturing children (born in first quarter of the year) likely to be chosen in the team (Figueiredo et al. 2009). In conclusion, current research indicates the presence of RAE in U12, U15 and U18 athletes compete in a championship. Thus, the overrepresentation in the early born of the athlete point out the bias of the selection toward athletes born later of the year. The over representation of early born players is suggested that they may have been selected based on their physical advantage and the selectors may have missed out skillful but physically less advantaged players.
6 Recommendation In the future of study, the prevalence of RAE should include physical assessment as well in all future studies. Besides, the potential moderators of the relative age effect should be investigating further. The future studies should create the implication on RAEs and how to removes RAEs from current sporting system to avoid any loss of potential among young athletes. Besides, the future research should also include and examine the place of birth of the athletes when RAE is present.
References Abel, E.L., Kruger, M.M., Pandya, K.: A relative age effect in men’s but not women’s professional Baseball: 1943–1954. Psychol. Rep. 109(1), 285–288 (2011). https://doi.org/10. 2466/05.PR0.109.4 Addona, V., Yates, P.A.: A closer look at the relative age effect in the national Hockey league. J. Quant. Anal. Sports 6(4) (2010) Barnsley, R.H., Thompson, A.H., Barnsley, P.E.: Hockey success and birth date: the relative age effect. Can. Assoc. Health Phys. Educ. Recreat. 51, 23–28 (1985) Barnsley, R.H., Thompson, A.H.: Birthdate and success in minor Hockey: the key to the NHL. Can. J. Behav. 20(2), 167 (1988) Bell, J.F., Massey, A., Dexter, T.: Birthdate and ratings of sporting achievement: analysis of physical education GCSE results. Eur. J. Phys. Educ. 2(2), 160–166 (1997) Del Campo, D.G.D., Vicedo, J.C.P., Villora, S.G., Jordan, O.R.C.: The relative age effect in youth soccer players from Spain. J. Sport. Sci. Med. 9, 190–198 (2010) Cobley, S., McKenna, J., Baker, J., Wattie, N.: How pervasive are relative age effects in secondary school education? J. Educ. Psychol. 101(2), 520–528 (2009) Delorme, N., Boiche, J., Raspaud, M.: Relative age and dropout in French male soccer. J. Sports Sci. 28(7), 717–722 (2010)
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Helsen, W.F., Baker, J., Michiels, S., Schorer, J., Van Winckel, J., Williams, A.M.: The relative age effect in European professional soccer: did ten years of research make any difference? J. Sports Sci. 30(15), 1665–1671 (2012) Mulazimoglu, Olcay: The Relative Age Effect (RAE) in youth and professional soccer players in Turkey. Anthropologist 18(2), 391–398 (2014) Salinero, J.J., Pérez, B., Burillo, P., Lesma, M.L.: Relative age effect in European professional Football. Analysis by position. J. Hum. Sport Exerc. 8(4), 966–973 (2013) Sprietsma, M.: Effect of relative age in the first grade of elementary school on long-term scholastic results: international comparative evidence using PISA 2003. Educ. Econ. 18(1), 1– 32 (2010) Ulbricht, A., Fernandez-Fernandez, J., Mendez-Villanueva, A., Ferrauti, A.: The relative age effect and physical fitness characteristics in German male Tennis players. J. Sports Sci. Med. 14, 634 (2015) Wattie, N., Schorer, J., Baker, J.: The relative age effect in sport: a developmental systems model. Sports Med. 45(1), 83–94 (2015)
Human Performance
The Acute Effects of Exercises Order During Upper-Lower Body Alternated Supersets Among Trained Men Muhammad Hannan Sazali(&), Mohamad Shahrul Azzfar, Nur Ikhwan Mohamad, and Ali Md. Nadzalan Faculty of Sports Science and Coaching, Sultan Idris Education University, Tanjong Malim, Malaysia [email protected]
Abstract. The aim of this study was to determine and compare the acute effects of exercise order during upper-lower body alternated supersets. This study was conducted by using quantitative time series experimental design. Twenty resistance-trained men performed different exercises order of upper body (bench press) and lower body (squat) exercises; (i) upper body to lower body (order A) and (ii) lower body to upper body (order B) in random arrangement for three sets with 120 s rest inter-set. All participants performed both exercises at 75% of their one repetition-maximum (1RM) value. Muscles activation and repetitions completed were recorded during both exercises order. Repeated measure analysis of variance (ANOVA) was used to analyse the different of all variables. Results showed order A produced higher upper body muscles activation (pectoralis major: q < .05, triceps brachii: q < .05) and number of repetitions completed (q < .05) in bench press for all three sets compared to order B. In contrast, order B showed higher lower body muscles activation (rectus femoris: q < .05, biceps femoris: q < .05) in squat compared to order A. Number of repetitions completed during squat were higher during order B compared to order A in the first set, q < .05. In conclusion, the results of this study suggested that the order of exercises performed in a resistance training session will determine the benefits gained. The findings of this study could be used as guideline for individuals involved in strength and conditioning to plan a better resistance training program for achieving their own specific goals. Keywords: Exercises order Repetition completed
Bench press Squat Muscle activation
1 Introduction Resistance training has been proven to be effective in improving physical fitness especially muscular strength [1, 2]. In order to enhance the effectiveness of resistance training, manipulation of training variables is deemed to be important. Previous researches has shown the different responses and adaptations when manipulating training program variables [3, 4].
© Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 83–90, 2020. https://doi.org/10.1007/978-981-15-3270-2_9
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One of the variables in resistance training is exercise order. Exercise order refers to the sequences of how the exercises been perform during training. Large muscle groups exercises had been recommended to be performed at the beginning of the training session followed by small muscle groups exercise because this exercise sequence will result in the ability to use the heaviest resistances possible when performing the exercises of the large-muscle group and may result in great long term strength gains [5, 6]. For a total body workout, bench press is among the recommended exercises to be performed for upper body while squat for the lower body. Finishing bench press for three sets followed by three sets of squats may take some times as there are other exercises to be performed too. Thus, implementing an alternated supersets might be a better way to reduce time of training. The question arise now, if the alternated supersets want to be implemented, which exercise need to be performed first? Is there any different of effects if the order of exercises is been manipulated? Until now, as to the author’s knowledge, lack of studies have been conducted on investigating the muscle and number of repetitions that can be completed during the alternated supersets, in which, the value of all variables are important as it will provide possible future adaptations such as hypertrophy and strength adaptations of the trained muscles. Thus, this study attempted to examine the acute effects of exercises order during upper-lower body alternated supersets among trained men.
2 Methodology 2.1
Participants
Twenty recreationally resistance-trained men were recruited for this study based on volunteerism. All participants must had at least six months experience involving in resistance training. All participants were from 20 to 25 years old. Besides that, all participants were in good health and do not have any injuries in the past 12 months. Participants were divided into two groups of exercises order by using counter-balance grouping technique, to avoid order effects. After finished their first session of exercises order, the crossover technique were done for second session to perform the different exercises order, Order A (n = 20) and Order B (n = 20). All participants were recruited after fulfilling the requirement in the inclusion and exclusion criteria. Then, both group were randomly selected through ticket draw to decide which type of exercises order they will perform first. Physical Activity Readiness Questionnaire (PAR-Q) and inform consent form were given to the participant to understand the purpose, procedure, and the risk involving in the study. The importance of the study was explained to the participants before starting the data collection. Before the data collection, all participants underwent one familiarization session to make sure the technique of squat and bench press were correct. 2.2
Squat and Bench Press Procedure
As participants need to lift 80% load of their maximal ability, one repetition maximum test was conducted for both the squat and bench press. The 1RM test was conducted by
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referring to the protocols provided by [7]. After obtaining the 1RM value, each participants’ 80% value for both exercises were calculated so that each participant will lift the correct amount of load. Squat was performed in a power rack to improve safety. Participants put the barbell on their mid portion of trapezius and at the back of deltoid. Participants were needed to grasped the barbell at their own preferred and comfortable point (Fig. 1). Participants were needed to flex their knee to lower the barbell until the bottom of the thighs were parallel to the floor (Fig. 2). Next, participants need to extend their knee to ascend back to the starting position (Fig. 1). This full movement was regarded as one repetition. Bench press test was also conducted in a power rack. Participants lie down on the bench and position themselves so that their eyes is parallel with the barbell. Participants were needed to grasped the barbell at their own preferred and comfortable point (Fig. 3). Participants need to lower the barbell through elbow flexion until the barbell was approximately touched the chest (Fig. 4). Then, the barbell need to be raised back to the starting position (Fig. 3). This full movement was regarded as one full repetition.
Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
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EMG Procedure
Electromyography (EMG) method was used to obtain the muscle activation data. EMG electrodes (Trigno, Delsys, USA) were placed at the dominant side triceps brachii and pectoralis major during bench press, while during squat, electrodes were placed at rectus femoris and biceps femoris. Muscle determination and electrode placement procedure were based on the surface EMG for non-invasive assessment of muscles (SENIAM) [8]. A qualified physiotherapist was presented to help in determining the right location of muscles that was involved in this research. The EMG setting was based on the previous study been conducted [9, 10]. EMG reading was obtained from the movement start until finish. EMG value was presented in mean of muscle activation from the MVC value. 2.4
Data Analysis
Descriptive statistics were used to analyze mean and standard deviation of participants’ data. To compare the number of repetitions and EMG data, repeated measure analysis of variances (ANOVA) was conducted. a-level of q < 0.05 was set as the significant value. All statistical analysis was performed using Statistical Package for the Social Science (SPSS) version 23 for Windows software.
3 Results Table 1 showed the physical characteristic profile of participants involved in this study. Table 1. Physical characteristic profile of participants involved Variables (N) Age (yrs) 20 Body mass (kg) 20 Height (m) 20 20 BMI (kg∙m−2) Bench press 1RM (kg) 20 Squat 1RM (kg) 20
3.1
Minimum Maximum Mean ± SD 20.00 25.00 21.30 ± 1.42 47.00 74.00 61.50 ± 7.06 1.58 1.88 1.70 ± 6.10 18.07 24.80 21.37 ± 1.99 75.00 90.00 84.25 ± 4.06 90.00 100.00 97.00 ± 3.40
Comparison of Muscles Activation Between the Exercises Order
Table 2 showed the EMG data of both exercises order during set 1. Analysis of the dominant upper and lower body showed that the significant differences were found in all the following muscles activity variables between the exercises order: (i) pectoralis major, F(1,19) = 39.14; q < 0.000, (ii) triceps brachii, F(1,19) = 27.70; q < 0.000, (iii) rectus femoris, F(1,19) = 692.99; q < 0.000, (iv) biceps femoris, F(1,19) = 526.85; q < 0.000.
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Table 2. Comparison of muscles activation between the exercises order for set 1 Muscles Order A Pectoralis Major Mean EMG (%) 58.72 ± Triceps Brachii Mean EMG (%) 34.98 ± Rectus Femoris Mean EMG (%) 47.46 ± Biceps Femoris Mean EMG (%) 29.11 ± *Result is significant when q < 0.05
7.79 5.38 15.08 7.49
Order B 53.81 ± 30.99 ± 51.01 ± 32.57 ±
8.86 7.34 14.91 7.59
Sig (q) 0.000* 0.000* 0.000* 0.000*
Table 3 showed the EMG data of both exercises order during set 2. Analysis of the dominant upper and lower body showed that the significant differences were found in all following muscles activity variables between the exercises order: (i) pectoralis major, F(1,19) = 42.12; q < 0.000, (ii) triceps brachii, F(1,19) = 40.46; q < 0.000, (iii) rectus femoris, F(1,19) = 292.92; q < 0.000, (iv) biceps femoris, F(1,19) = 132.04; q < 0.000. Table 3. Comparison of muscles activation between the exercises order for set 2 Muscles Order A Pectoralis Major Mean EMG (%) 56.09 ± Triceps Brachii Mean EMG (%) 32.61 ± Rectus Femoris Mean EMG (%) 44.54 ± Biceps Femoris Mean EMG (%) 26.36 ± *Result is significant when q < 0.05
7.87 5.19 14.62 7.54
Order B 51.40 ± 28.46 ± 48.13 ± 29.54 ±
8.43 6.61 14.73 7.62
Sig (q) 0.000* 0.000* 0.000* 0.000*
Table 4 showed the EMG data of both exercises order during set 3. Analysis of the dominant upper and lower body showed that the significant differences were found in all following muscles activity variables between the exercises order: (i) pectoralis major, F(1,19) = 44.66; q < 0.000, (ii) triceps brachii, F(1,19) = 38.66; q < 0.000, (iii) rectus femoris, F(1,19) = 120.65; q < 0.001, (iv) biceps femoris, F(1,19) = 122.544; q < 0.000. Table 4. Comparison of muscles activation between the exercises order for set 3 Muscles Order A Pectoralis Major Mean EMG (%) 52.48 ± Triceps Brachii Mean EMG (%) 29.64 ± Rectus Femoris Mean EMG (%) 42.15 ± Biceps Femoris Mean EMG (%) 23.52 ± *Result is significant when q < 0.05
3.2
7.06 4.84 14.51 7.84
Order B 47.74 ± 25.57 ± 45.03 ± 26.54 ±
8.06 5.95 14.49 7.76
Sig (q) 0.000* 0.000* 0.001* 0.000*
Number of Repetitions Completed Between Exercises Order
Table 5 showed the comparison of the repetitions completed during bench press between the exercises order. The pairwise comparison analysis of the dominant upper
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limb between order A and order B was showed the significant differences on the repetitions completed for bench press: (i) set 1, F(1,19) = 103.26; q < 0.000, (ii) set 2, F(1,19) = 137.14; q < 0.000 and (iii) set 3, F(1,19) = 62.81; q < 0.000. Table 5. Comparison of repetitions completed between exercises order for bench press Sets Order A Order B Sig (q) 1 9.75 ± 1.92 7.25 ± 1.62 0.000* 2 9.00 ± 1.86 6.3 ± 1.34 0.000* 3 8.05 ± 2.01 5.3 ± 1.30 0.000* *Result is significant when q < 0.05
Table 6 showed the comparison of the repetitions completed during squat exercises between the exercises order. The pairwise comparison analysis of the dominant lower limb between order A and order B were showed the significant differences on the repetitions completed for squat exercises during set 1, F(1,19) = 13.57; q < 0.002. However, there were no significant differences between the exercises order A and B during set 2 and set 3: (i) set 2, F(1,19) = 4.13; q < 0.056, and (ii) set 3, F(1,19) = 4.13; q < 0.056. Table 6. Comparison of repetitions completed between exercises order for squat Sets Order A Order B Sig (q) 1 11.85 ± 1.66 12.35 ± 1.50 0.002* 2 11.20 ± 1.51 11.45 ± 1.39 0.056 3 10.30 ± 1.34 10.55 ± 1.47 0.056 *Result is significant when q < 0.05
4 Discussions EMG is a method to detect the intentional or voluntary activation in the muscles. Voluntary activation is affected by both the motor unit frequency and the level of muscle recruitment and is almost related to the unfatigued muscle force production [11, 12]. In this study, the percentage of mean EMG data for pectoralis major, triceps brachii, rectus femoris, biceps femoris activities were determined and compared between exercises order and between sets. All of these conditions applied only to the dominant upper and lower limb. The comparison of muscles activation for all three sets showed the significant differences results between exercises order A and order B, q < 0.001 for all muscles. However, the pattern of the percentage for both part of muscles activation were different because the activation of pectoralis major and triceps brachii were higher during order A, but the activation of rectus femoris and biceps femoris were higher during order B. Even so, the percentage difference of lower body musles activation were not much as both the upper body muscles.
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This outcome pattern may occur as each training sequence begins with different exercise. This will give an advantage for all participant to perform the best trial in every first type of exercise compared to the second type of exercise in both order. Based on both exercises order, the muscles activities during second exercise decreased in every sets. Even though the analysis results showed significant differences for all muscles, the percentage difference of EMG results for lower body muscles were not as much as EMG results for upper body muscles. This showed that, exercise order starting with upper body had more effect to the muscles improvement during resistance training. The decrease in muscles activation on second exercises during opposite exercises order may occur due to neuromuscular fatigue of some muscles that compensated for increased some motor unit recruitment of other muscles in an attempt to maintain performance after doing the first exercise. The number of repetitions completed was different between the two exercises during the training program. The results showed that, number of repetition for bench press exercise significantly decreased during exercise order B compared to exercises order A for all three sets. This pattern of a results between order A and order B in the total mean number of repetitions for bench press indicated that different multi-joint exercises were negatively impacted the performance. Performance refers to the ability to perform the allotted number of repetitions without stopping to rest [13]. The number of repetitions for squat exercise did not show significant different for set two and set three between both exercises order. Even though there were some improvement on the number of repetitions during squat exercise, but only small differences were found between both order A and B. The performance of participants were quite the same for squat exercise even it was done first or second in exercises order. This result was similar as other previous study that found no significant differences on number of repetitions for lower body exercise [14]. However, the analysis for number of repetitions completed on squat exercises in set one showed significant improvement during exercise order B compared to exercise order A. This was due to the squat exercise that was done first in order B and it gave some advantage for all participants that still not affected by other element such as fatigue before starting the exercises program and this allows them to do their best performance in producing more number of repetitions completed for squat exercise in the first sets of order B.
5 Conclusions Based on the results, performing a an alternated upper-lower body superset starting with upper body exercise first was suggested to be more suitable to be adopted with greater number of repetitions completed along with more muscle activation, starting upper body exercise first would be more preferable to be associated with improvement in muscle development.
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Body Composition and Muscular Performance of Malaysian Young Male State Level Weightlifting, Cycling and Squash Athletes Norsuriani Samsudin , Foong Kiew Ooi(&) and Chee Keong Chen
,
Exercise and Sports Science Programme, School of Health Sciences, Health Campus, Universiti Sains Malaysia, 16150 Kelantan, Malaysia [email protected]
Abstract. The present study investigated the differences in body composition and muscular performance of Malaysian young male state level weightlifting, cycling and squash athletes. Forty-four participants (mean age: 17.1 ± 1.6 years old) were divided into sedentary control, weightlifting, cycling and squash groups with 11 participants for each group. Participants’ body composition, hand grip strength, back and leg strength as well as resting heart rate and blood pressure were determined. One way ANOVA was performed for statistical analysis. The present study found that weightlifting group exhibited statistically significant higher body weight (p < 0.001) compared to cycling and sedentary control group. Weightlifting group also showed higher percentage of body fat and fat-free mass (p < 0.05) when compared to the cycling group, and higher fat-free mass (p < 0.01) than the sedentary control group. In addition, weightlifting athletes showed significantly greater hand grip strength (p < 0.01), as well as back and leg strength (p < 0.01) compared to sedentary controls, cycling and squash athletes. Cyclists had lower resting heart rate compared to weightlifting and squash athletes. The present study findings implying that body composition and muscular performance of the athletes are dependent on sports events they were involved in. Keywords: Body composition Fat free mass Body fat Body mass index Muscular strength
1 Introduction Body composition is a vital health component among athletes. Maintaining an appropriate body composition among young and adolescent athletes can lead to improved cardiorespiratory fitness [1] and strength [2]. Assessment of body fat has been used to determine optimal body weights for athletes [3]. Sundgot-Borgen et al. [4] and Ackland et al. [5] reported that there are no general optimum values for percentage of fat mass in different types of sports, and there is no ‘gold standard’ method to evaluate body composition among athletes. However, the aim of the athletes is to develop good dietary habits for obtaining healthy body weight that can be maintained during competitive seasons [6]. According to Kruschitz et al. [7], the use of © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 91–99, 2020. https://doi.org/10.1007/978-981-15-3270-2_10
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subcutaneous fat measurement and percentage of total body fat could be more effective than body mass index assessment in assessing fatness and obesity in active individuals. Weightlifting is well known as a type of weight bearing sport that involves highintensity loading forces and demands forceful strength and power which require multiple joint movement and whole body lifting [8]. During the snatch and clean and jerk (C&J) lifts, the weightlifters are required to generate high forces, which consequently produce high ultimate power outputs and contractile impulses [9]. Cycling is a type of non-weight-bearing and aerobic exercise which involves repetitive intensity motion. The spines of the cyclists are suspended evenly between the handlebars and the seat during cycles, and their feet do not contact the surface of the ground while cycling. Therefore, there are no normal weight-bearing ground reaction forces. However, the cyclists may experience high mechanical loading at the hip from the stress forces induced by high-intensity contractions by the leg and hip muscles during cycling [10]. Squash involves repetitive weight-bearing, impact loading, as well as accelerating and decelerating movements. During the stroke, the arms of squash players are loaded with impacts with rapid, frequent, and multidirectional leg movements. Thus, it is believed that the movements of squash players produce high muscular contraction at hip and shoulder [11]. Weightlifting, cycling, and squash are popular activities among youth. It is hypothesised that there are variations in body composition and muscular performance such as handgrip strength and back and leg strength of these three types of sports. To date, information on these fitness components in Malaysian young athletes of these three sports are limited. Therefore, this present study was proposed to assess body composition, and muscular performance of Malaysian young male weightlifting, cycling and squash athletes.
2 Methodology 2.1
Participants’ Recruitment
Forty-four male athletes participated in this present study. The inclusion criteria of the weightlifting, cycling and squash athletes were Malaysian males with age ranged between 15 to 20 years old. The weightlifting, cycling and squash participants were involved in weightlifting, cycling and squash training respectively at least 3 years and currently representing Malaysia Kelantan state in weightlifting, cycling, and squash competitions. The road cyclists was recruited in this study. Meanwhile, the inclusion criteria of the sedentary control participants were Malaysian male participants, with age ranged between 15 to 20 years old, were not involved in any competition and exercised less than 2 times per week. Written informed consent was provided by the participants who fulfilled the inclusion criteria. The exclusion criteria of the all participants were having any acute and chronic diseases such as asthma, stroke, diabetes and heart problems. The present study was approved by the Human Research Ethics Committee of Universiti Sains Malaysia (USM) (JEPeM Code: USM/JEPeM/17120709).
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Experimental Design
The study employed purposive sampling method, and it was a cross-sectional study. The athletes were recruited through coaches. The participants were match of their age and being divided into four groups with 11 participants for each group. The groups were sedentary control group, weightlifting group, cycling group, and squash group. Participants’ body composition, resting heart rate, blood pressure, hand grip strength, and back and leg strength were measured in this study. 2.2.1
Body Composition, Resting Heart Rate and Blood Pressure Measurements A stadiometer (Seca 220, Hamburg, Germany) was used to determine participants’ body height (m). For the height measurement, the reliability value is 0.949 [12]. Meanwhile, a body composition analyser (Tanita model TBF-410, Japan) was used to measure participants’ body weight (kg) and body composition such as percent body fat (% BF) and fat-free mass (FFM, kg). The reliability values for body composition analyser of body mass (kg) and body fat (%) are 1.00 and 0.93 on their respectively [13]. Participants’ resting heart rate (beats.min−1) and blood pressure, i.e. systolic and diastolic blood pressures (mmHg). Were measured by using an automatic upper arm blood pressure monitor (TM-2540, San Jose, USA). For the blood pressure monitor, the reliability values of systolic and diastolic blood pressure are 0.729 and 0.669 respectively [14]. All the measurements were measured during off-season phase. 2.2.2 Handgrip Strength, and Back and Leg Strength Measurements The participant’s handgrip strength (kg) for both dominant and non-dominant hand was measured by using a hand dynamometer (JAMAR J00105, USA). Firstly, participants were required to hold the dynamometer in the dominant hand. The participants were required to grip the dynamometer with maximum effort and maintained for 5 s while no other body movements were allowed. After three trials were completed, the same steps were applied to the non-dominant hand. Subsequently, the best result of the three trials was used for reflecting handgrip strength. The reliability for the Jamar dynamometer is 0.82 [15]. For the back and leg strength measurement, the participants were required to stand on the base of a back and leg dynamometer (Takei TKK 1858, Japan). Participants’ hold the centre of the bar with both hands, and the chain was adjusted so that participants’ knees were slightly bent. Subsequently, participants were required to pull the chain as hard as possible. Three attempts were repeated for each participant. The best result was used to reflect back and leg strength. The reliability of the back and leg strength dynamometer is 0.93 [16]. 2.3
Data Analysis
Statistical Package for Social Sciences (SPSS) version 24.0 was used for analysing data. One-Way ANOVA and Bonferroni post hoc test were used for determining the differences of measured parameters among the groups. Results are presented as means ± standard deviations (mean ± SD). Statistical significance was accepted at p < 0.05.
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3 Results Table 1 illustrates the mean age, body height, body weight, body mass index (BMI), percentage of body fat (% BF), fat-free mass (FFM), resting heart rate (RHR), systolic blood pressure (SBP) and diastolic blood pressure (DBP) of the participants in sedentary control, weightlifting, cycling and squash groups. There was a statistically significant higher value of body weight (p < 0.001) in the weightlifting group compared to cycling and sedentary control group. Meanwhile, there was a statistically significant higher value of body mass index (p < 0.05) in the weightlifting group compared to all the other groups. Weightlifting group also demonstrated higher percentage of body fat and fat-free mass (p < 0.05) when compared to the cycling group and higher fat-free mass (p < 0.01) than the sedentary control group. It was observed that cycling group showed a lower resting heart rate (p < 0.05) compared to all the other groups. There were no statistically significant differences in body height, systolic and diastolic blood pressure among sedentary control, weightlifting, cycling, and squash groups.
Table 1. Mean age, body height, and weight, body mass index (BMI), body composition, resting heart rate (RHR) and blood pressure of the participants in sedentary control, weightlifting, cycling, and squash groups Weightlifting Cycling group Squash group Sedentary group (n = 11) (n = 11) (n = 11) control group (n = 11) Age (years) 17.1 ± 1.6 17.5 ± 1.7 16.9 ± 1.5 16.8 ± 1.7 Body height (m) 164.6 ± 7.6 165.2 ± 5.9 165.1 ± 5.9 168.1 ± 9.8 Body weight (kg) 54.0 – 13.1 84.7 – 23.3*** 51.8 – 9.6 ### 67.12 ± 10.1 BMI (kg/m2) 20.2 – 3.8 36.8 – 6.8*** 18.9 – 2.2### 23.8 – 5.5 # Body fat (%) 21.2 ± 6.5 27.2 – 12.0 16.5 – 6.1 # 22.7 ± 7.4 FFM (kg) 41.3 – 6.0 60.5 – 15.9** 43.3 – 8.6 ## 51.7 ± 12.7 RHR (beats.min−1) 73.2 – 9.8 78.9 – 10.9 61.3 – 6.4*## 78.6 – 11.9&& SBP (mmHg) 123.8 ± 7.9 130.7 ± 13.5 123.8 ± 27.0 129.0 ± 8.8 DBP (mmHg) 71.0 ± 7.9 72.0 ± 7.3 69.6 ± 7.5 74.9 ± 6.5 All values are expressed as means ± S.D *p < 0.05, **p < 0.01, ***p < 0.001 significantly different from sedentary control group #p < 0.05, ##p < 0.01, ###p < 0.001 significantly different from weightlifting group &&p < 0.01 significantly different from cycling group Abbreviations: BMI = Body mass index; FFM = Fat free mass; RHR = Resting heart rate; SBP = Systolic blood pressure; DBP = Diastolic blood pressure Variables
Figures 1 and 2 exhibit the means of handgrip strength and back and leg strength measurements in sedentary control, weightlifting, cycling, and squash groups. Weightlifting group exhibited statistically significant greater handgrip strength (p < 0.01) in non-dominant hand, as well as back and leg strength compared to
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sedentary control, squash and cycling groups. In addition, the weightlifting group also exhibited statistically significant higher (p < 0.01) handgrip strength in the dominant hand compared to sedentary control and cycling groups. 70
***
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Dominant hand Non-dominant hand
***
50
##
40
###
###
30 20 10 0 Sedentary control
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Fig. 1. Handgrip strength measurements in sedentary control, weightlifting, cycling, and squash group (All values are expressed as means ± S.D. ***p < 0.001 significantly different from sedentary control group. ##p < 0.01, ###p < 0.001 significantly different from weightlifting group)
200
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Back and leg strength (kg)
180 160 140
###
##
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120 100 80 60 40 20 0 Sedentary control
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Fig. 2. Back and leg strength measurements in sedentary control, weightlifting, cycling, and squash groups (All values are expressed as means ± S.D. ***p < 0.001 significantly different from sedentary control group. ##p < 0.01, ###p < 0.001 significantly different from weightlifting group)
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4 Discussion Body composition is a commonly studied fitness parameter among athletes. A low body fat percentage has been reported to be related to increased endurance performance, while large muscle mass to be related to strength and power performance [17]. Body composition is an important element to success in athletic performance. Generally, specific sports requires different body types, body structures and weights for maximal performance. In the present study, the frequency of the training program for the weightlifting athletes was six times in a week, with two sessions of two hours per day. High pull snatch, jerk press, push jerk, high pull clean, front squat, snatch comb, snatch balance, jerk block, back squat, and weight training were included in their training program. Meanwhile, the cyclists were trained for six times per week, with two hours of session per day. Strength training, endurance training, agility, speed training, and interval training were examples of types of training for increasing cyclists’ fitness level. Regarding training program for squash athletes, they performed their training six times per week with three hours session per day. Fitness training for them included jogging, sprinting, court run, endurance training, and weight training, while training for skills included agility, ladder drill, close drill, open drill, feeding, pattern drill, ghosting and shadow drill. In present study, it was observed that weightlifting group showed statistically significant higher body weight, fat and fat-free mass compared to endurance cycling group. Consistently, Heyward and Wagner [18] mentioned that low body fat is important in endurance events such as cycling, while a large muscle mass is crucial in power and strength events such as weightlifting. Siahkouhian and Hedayatneja [19] reported that there were significantly moderate positive correlations between body composition, anthropometric components and weightlifting performance. The strong positive correlation between lean body mass and weightlifting performance implying that lean body mass is an important element in weightlifting. Burdukiewicz et al. [20] which investigated body composition in Polish Championship female weightlifters found that female weightlifters showed greater muscle and fat mass development. Consistently, the present study also found that weightlifting group had high values of body weight, body fat and fat-free mass, and implying that these few anthropometric and body composition parameters are crucial parameters in weightlifters who are required to lift a heavy load. The present study showed that the endurance cycling group exhibited lower resting heart rate than sedentary controls, weightlifters and squash athletes. Generally, it is well known that weightlifting is a type of weight bearing sport that involves high-intensity loading forces with high intensity and short duration and depending on anaerobic energy systems [8]. Cycling is a non-weight-bearing and aerobic type of sport which involves repetitive intensity motion, which requires mixed anaerobic and aerobic metabolic responses, and estimated about 25% anaerobic and 75% aerobic metabolism. There are repetitive low to moderate intensity movements throughout cycling match and training [21]. Conversely, squash has been reported as being anaerobic predominantly [22]. It is speculated that cyclists greatly rely on aerobic energy system, and the
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cycling training with prolonged duration resulting in high cardiovascular fitness with lower resting heart rate in the cyclists compared to weightlifters and squash athletes as seen in the present study. Carter et al. [23] mentioned that one of the physiological adaptation of endurance training is lower resting heart rate as observed in cycling group. This is attributed through the dominant of parasympathetic activities at rest. Additionally, the result showed the different type of training by the different athletic group did not show any effect on the resting systolic and diastolic blood pressure. In the present study, weightlifting group exhibited statistically significant greater handgrip strength in non-dominant hand, as well as back and leg strength compared to sedentary control, squash and cycling groups. In addition, the weightlifting group also exhibited statistically significant higher handgrip strength in the dominant hand compared to sedentary control and endurance cycling groups. These findings implying that great strength of the handgrip, as well as back and leg muscles are produced with weightlifting movements. Higher handgrip strength observed in weightlifters could be due to the nature of the sport where the weightlifters are required to grip tightly the barbell during lifting. During the snatch, the participants were required to lift the weighted barbell to an overhead position in one continuous movement with wide grip, whereas during the clean, the weightlifters were required to raise the barbell to the front of the shoulders in one continuous movement with shoulder-width grip. The lifting cannot be performed without maintaining the grip [24]. The present study finding was in agreement with previous studies by Masale and Sawant [25] which reported that handgrip value was high in weightlifting athletes. The present study finding also provides evidences that weightlifting elicited greater handgrip strength in weightlifters compared to endurance cycling which requires the cyclists to hold the handlebars during cycling, and squash which requires the players to grip the racquet during the play. Training in weightlifting focuses on development of the upper body muscle, i.e. shoulder and hand, as well as back muscle and lower body, i.e. leg strength. Back and leg strength is important during the catch phase as the weightlifter are required to catch the barbell on their shoulders while flexed the hip and knee into a full squat position. Then, the lifters recover from the position of full squat to prepare for the jerk phase. During this phase, the maximal strength of back and leg are required in order to lift the barbell in a vertical position to a standing position while the barbell is maintained in overhead position. It is speculated that prolonged period of weightlifting training resulting in the observable beneficial effects on handgrip strength, and back and leg strength of the weightlifters in the present study. This finding has provided the data on muscular strength and body composition of young male weightlifting, cycling and squash athletes. The current study has few limitations, such as the recruited athletes only represented state level, they were young athletes with limited age range, i.e. between 15 and 20 years old, and only male participants were involved. In conclusion, the present study evidenced weightlifting athletes have greater hand grip strength, and back and leg strength than cycling and squash athletes. Meanwhile, weightlifting group showed higher body weight, percentage body fat and fat-free mass
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than cyclists and squash athletes. These results also implying that body composition and muscular performance of the athletes are dependent on sports events they were involved in. Acknowledgment. The authors would like to express great appreciation to the coaches of Malaysia Kelantan weightlifting, cycling and squash state teams, and the athletes for their participation in this study. Special thanks to the staff of Exercise and Sports Science Laboratory, School of Health Sciences, Universiti Sains Malaysia for their assistance. There is no funding for this study. Competing Interests. There is no competing interests.
Ethical Approval. All procedures were approved by the Research and Human Ethics Committee of Universiti Sains Malaysia (JEPeM Code: USM/JEPeM/17120709).
References 1. Hogstrom, G.M., Pietila, T., Nordstrom, P., Nordstrom, A.: Body composition and performance: influence of sport and gender among adolescents. J. Strength Cond. Res. 26(7), 1799–1804 (2012) 2. Silva, A.M., Fields, D.A., Heymsfield, S.B., Sardinha, L.B.: Body composition and power changes in elite judo athletes. Int. J. Sports Med. 31, 737–741 (2010) 3. Torstveit, M.K., Sundgot-Borgen, J.: Are under- and overweight female elite athletes thin and fat? A controlled study. J. Med. Sci. Sport. Exerc. 44(5), 949–957 (2012) 4. Sundgot-Borgen, J., Meyer, N.L., Lohman, T.G., Ackland, T.R., Maughan, R.J., Stewart, A. D., Muller, W.: How to minimise the health risks to athletes who compete in weightsensitive sports review and position statement on behalf of the ad hoc research working group on body composition, health and performance, under the auspices of the IOC Medical Commission. Br. J. Sport. Med. 47(16), 1012–1022 (2013) 5. Ackland, T.R., Lohman, T.G., Sundgot-Borgen, J., Maughan, R.J., Meyer, N.L., Stewart, A. D., Muller, W.: Current status of body composition assessment in sport: review and position statement on behalf of the ad hoc research working group on body composition health and performance, under the auspices of the IOC Medical Commission. Sports Med. 42(3), 227– 249 (2012) 6. Manore, M.M.: Weight management for athletes and active individuals: a brief review. Sports Med. 45, 83–92 (2015) 7. Kruschitz, R., Wallner-Liebmann, S.J., Hamlin, M.J., Moser, M., Ludvik, B., Schnedl, W.J., Tafeit, E.: Detecting body fat – a weighty problem BMI versus subcutaneous fat patterns in athletes and non-athletes. PLoS ONE 8(8), e72002 (2013) 8. Storey, A., Smith, H.K.: Unique aspects of competitive weightlifting performance, training and physiology. J. Sports Med. 42(9), 769–790 (2012) 9. Garhammer, J.A.: Comparison of maximal power outputs between elite male and female weightlifters in competition. Int. J. Sport Biomech. 7, 3–11 (1991) 10. Faria, E.W., Parker, D.L., Faria, I.E.: The science of cycling factors affecting performance. Sports Med. 35(4), 313–337 (2005)
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11. Heinonen, A., Oja, P., Kannus, P., Sievanen, H., Manttari, A., Vuori, I.: Bone mineral density in female athletes representing sports with different loading characteristics of the skeleton. Bone 17, 197–203 (1995) 12. De Vriendt, T., Huybrechts, I., Ottevaere, C., Van Trimpont, I., De Henauw, S.: Validity of self-reported weight and height of adolescents, its impact on classification into BMIcategories and the association with weighing behaviour. Int. J. Environ. Res. Public Health 6 (10), 2696–2711 (2009) 13. Kutac, P.: Inter-daily variability in body composition among young men. J. Physiol. Anthropol. 34(1), 1–7 (2015) 14. Shepard, D.S.: Reliability of blood pressure measurements: implications for designing and evaluating programs to control hypertension. J. Chronic Dis. 34(5), 191–209 (1981) 15. Hamilton, G.F., McDonald, C.A., Chenier, T.C.: Measurement of grip strength: validity and reliability of the sphygmomanometer and jamar grip dynamometer. J. Orthop. Sport. Phys. Ther. 16(5), 215–219 (1992) 16. Ten Hoor, G.A., Musch, K., Meijer, K., Plasqui, G.: Test-retest reproducibility and validity of the back-leg-chest strength measurements. Isokinet. Exerc. Sci. 24(3), 209–216 (2016) 17. Heyward, V.H., Stolarczyk, L.M.: Applied Body Composition Assessment, 2nd edn. Human Kinetics, Champaign (1996) 18. Heyward, V.H., Wagner, D.R.: Applied Body Composition Assessment, 2nd edn. Human Kinetics, Champaign (1996) 19. Siahkouhian, M., Hedayatneja, M.: Correlations of anthropometric and body composition variables with the performance of young elite weightlifters. J. Hum. Kinet. 25, 125–131 (2010) 20. Burdukiewicz, A., Pietraszewska, J., Andrzejewska, J., Witkowski, K., Stachoń, A., Chromik, K., Maslinski, J.: Morphological differentiation and body composition in female judokas and female weightlifters in relation to the performed sport discipline. Sci. Martial Arts 6(2), 10–12 (2010) 21. Craig, N.P., Norton, K.I.: Characteristics of track cycling. Sports Med. 31(7), 457–468 (2001) 22. Sharp, C.: A testing time. Squash player intensity. Br. J. Sport. Med. 16, 26–27 (1988) 23. Carter, J.B., Banister, E.W., Blaber, A.P.: Effect of endurance exercise on autonomic control of heart rate. Sports Med. 33(1), 33–46 (2003) 24. Garhammer, J.: Weight lifting and training. In: Biomechanics of Sport, pp. 169–207. CRC Press Inc., Boca Raton (1989) 25. Masale, B.S., Sawant, V.A.: Physiological profile of trained weightlifters. Int. J. Phys. Educ. Sport. Sci. 6, 78–82 (2011)
Development of a Soccer-Specific Running Protocol for Young Soccer Players Siti Azilah Atan(&)
and Mohar Kassim
National Defence University of Malaysia, 57700 Kuala Lumpur, Malaysia [email protected]
Abstract. The aim of this study was to assess the reliability of a novel soccer simulation protocol (SSP), which was designed to replicate the activity pattern typically recorded in U15 soccer player’s match-play. Twenty male outfield soccer players (n = 20, 1.67 ± 0.4 m, 55.3 ± 8.4 kg) from the Sekolah Sukan Bukit Jalil (SSBJ) volunteered to participate in this study. The SSP was performed on two occasions to determine test-retest reliability. Sprint speed (kmh−1) was measured in one direction (15 m) using 5 Hz (with interpolated 10 Hz output) global positioning system unit. Physiological, physical capacity and perceptual scales were also monitored. The SSP running intensities were devised in a cyclical pattern required the participants to complete 4 20 min blocks of exercise separated by 3 min recovery. No significant difference was observed between trials in peak sprint speed (p = 0.930), perceptual scales (RPE; p = 0.835, FS; p = 0.751, FAS; p = 0.222), countermovement jump (p = 0.280) and heart rate (p = 0.330) between trials. The physiological and physical performance was observed repeatable and reliable (ICC = 0.85 to 0.98, SEM 0.01 to 0.6). In conclusion, the SSP’s appears to be reliable protocol that replicated the physical demands of youth soccer match play. Keywords: Football system
Intermittent Field test Youth Global positioning
1 Introduction In recent years, there has been a growing interest in examining performances of young soccer players within various sports science disciplines (Figueiredo et al. 2009; Hirose 2009; Papanikolaou 2011; Timmons et al. 2007). Surprisingly, less is known about the potential effects of ergogenic aids or training interventions in young players. This is particularly important because adolescents have different physical and physiological processes attributed to soccer performance due to lower aerobic and anaerobic capacity, lower glycogen stores and less well-developed thermoregulatory processes (Alvarado 2005). For adults, soccer simulation protocols (SSP) have been used to investigate several aspects of soccer performance (Ali et al. 2007a). For instance, McGregor et al. (1999) and Ali et al. (2007a) have shown that fluid and carbohydrate ingestion, respectively, help to prevent deterioration in skill performance in well-trained male players.
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During actual match play, physical and physiological demands can vary between games due to environmental conditions, strength of the opposition and the fitness of players (Drust et al. 2000). Therefore, in order to understand for example, the effects of various ergogenic aids upon soccer performance (e.g. preparatory or half-time strategies), the influence of training intervention strategies, or as a test for athlete readiness to return to match-play following rehabilitation (Russell et al. 2011), the development of a valid and reliable SSP for young players is required. A suitable SSP will re-create and standardise movement patterns and physiological demands in soccer (Russell et al. 2011) and researchers will be able to control and manipulate certain variables. To generate a more refined protocol, the SSP must be developed from match analysis data (Bangsbo et al. 1991; Bradley et al. 2009). In addition, to enhance ecological validity, the protocol must simulate specific movement patterns, total distance covered, the duration of playing and recovery intervals as well as the physiological responses observed in match-play. Few soccer simulation protocols have been developed for young players. Thatcher and Batterham (2004) devised a 90-min simulation protocol using a non-motorised treadmill for under 19-year-old (U19) players. Although the heart rate response was similar to a soccer match, treadmills only allow unidirectional running (no sideways and backward movement), involve no turning, induce less eccentric muscle contractions, do not allow true maximal speed to be attained (Drust et al. 2000; Sirotic and Coutts 2007), and therefore, lack ecological validity relative to overground running (Williams et al. 2009). Phillips et al. (2010) modified the Loughborough Intermittent Shuttle Test (LIST; Nicholas et al. 2000) to investigate the effects of carbohydrateelectrolyte (CHO-E) ingestion on various parameters in 12-year-old soccer players. They reduced the SSP to a shorter time of 60 min compared to the original 90-min LIST. Meanwhile, Russell et al. (2011) adopted a similar free-running approach with additional components such as a 15-min passive recovery period (to account for a halftime break), passing, dribbling and shooting skills incorporated within a 90-min protocol. Even though shuttle running offers a more appropriate assessment of match play, these protocols were not based on match analysis data and actual playing time in youth soccer and no reliability or validity information was provided. Given the limitations associated with assessing young players, we have devised novel shuttle-running simulations for youth players based on match analysis data for U15. This protocol was designed to simulate the total distance covered, physiological demands and match activity patterns observed during match-play. Therefore, this study aims to assess the reliability this new simulation protocol adaptations for use with young soccer players aged 15 years old. It was hypothesised that the SSP’s physiological and physical measurements could be similar between trials.
2 Materials and Methods 2.1
Subjects
The SSP’s data was collected on twenty (n = 20) outfield players representing Sekolah Sukan Bukit Jalil (SSBJ) (Height 1.67 ± 0.4 m, body mass (BM) 55.3 ± 8.4 kg)
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volunteered to participate in the study. The participants were competitive in local and international soccer tournaments. Written consent form was obtained from the participant’s parents/guardian after being thoroughly informed the benefits and potential risks of the study as all the participants were under age of 18 (15.6 ± 0.4 years); the study was approved by the local institutional ethics committee. 2.2
Familiarisation
All participants attended one preliminary session to familiarise themselves with the protocol procedures and perceptual scales; ratings of perceived exertion (RPE; Borg 1998), Feeling scale (FS; Hardy and Rejeski 1989) and Felt Arousal scale (FAS; Svebak and Murgatroyd 1985) along with height and body mass (BM) measurements. 2.3
Match Analysis Data
The match analysis data was collected in 30 players competing within the Auckland Football Federation (AFF) Metropolitan League during 2 competitive matches using 5 Hz (with interpolated 10 Hz output) global positioning system (Atan et al. 2016) (refer Table 1). The match played in agreement with the rules outlined by the Federation Internationale de Football Association (FIFA). The U 15 played 2 40 min periods with rolling substitution policy. The SSP data was developed based on the relative values (mmin−1) considering to rolling substitution policy (Table 1) in youth match play. Furthermore, the relative values are considered appropriate to truly represent the typical total distance covered in U 15 soccer match play.
Table 1. The total distance covered, percentage of distance and time spent in each movement in actual match-play (match) and the soccer simulation protocol Activity
Distance
Match (mmin−1) 7600 – 1800 2400 2500 600 300
% of distance in each match activity Protocol (m) Match Protocol 7800 – – – 1560 24% 20% 2340 31% 30% 2340 33% 30% 780 8% 10% 360 4% 4.6% 420 5.4%
% of time spent in each match activity Match Protocol
TD Standing 14% 15% Walking 39% 34% LIR 27% 28% MIR 16% 15% HIR 3% 3.8% Sprinting 1% 1.5% Utility movement *4% 3.5% *Abbreviation TD = total distance, LIR = low intensity running, MIR = medium intensity running, HIR = high intensity running *Utility movement was adapted from Capranica et al. (2010) which is 4% of time spent in a soccer match
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Experimental Design
Data was collected during the competitive season (May–June 2016) and took place on outdoor artificial grass pitches with no differences seen in environmental conditions between trials. Following familiarisation, the SSP was performed in full on two occasions (separated by 7 days). Participants were asked to refrain from strenuous physical activity 24 h before each trial, record dietary intake (24 h before the first protocol) and required to replicate the same diet prior to trial 2. A weather station (ETHG-912; Oregon Scientific, USA) was used to record the temperature and humidity during trials. Mean temperatures and relative humidity recorded were 32.2 ± 2.1 °C and 61 ± 13.2% respectively. On arrival, participants emptied their bladder and a small sample of urine was used to measure hydration status via handheld refractometry (Sur-Ne, Atago Co. Ltd., Japan). BM was then recorded using electronic weighing scales (HV200KGL NTEP, Industrial Balance, USA). After donning the 5 Hz GPS unit (with interpolated 10 Hz output) and heart rate strap (GPSports Systems, Australia), participants performed 10 min of a standardised warm-up, consisting of jogging, striding and dynamic stretching. Participants consumed 5 mLkg−1 BM of water before commencing the main trial from the bottles (sipper bottles) provided with each participant’s bottle was clearly labelled (see Fig. 1). The SSP performed 4 20-min ‘blocks’ of exercise separated by 3 min recovery (Fig. 1). The FS and FAS scales were administered prior to exercise. Within the rest periods between exercise blocks, RPE, FS and FAS (in that order) and CMJ were administered and participants ingested the equivalent of 2 mlkg−1 BM of water. Heart rate (HR) was monitored continuously at 5 s intervals (GPSports Systems, Australia) and BM was again obtained on completion of the protocol.
Fig. 1. Schematic representation of the under 15 soccer simulation protocol (SSP)
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SSP Speed
The exercises include low and high intensity activities based on the match speed thresholds (middle range) for the U 15 such as walking, low intensity running, medium intensity running, and high intensity running, sprinting as well as utility movements (Table 2). Speeds for each activity were dictated via an audible signal (and voice) from software specifically developed for this test. Table 2. Order and running speeds for SSP U 15
Exercise duration
80 min protocol Blocks 4 20 min Order 4 15 m 4 15 m 1 15 m 4 15 m 1 15 m
Cycle 13 cycles Speed 1.77 ms−1 3.33 ms−1 4.27 ms−1 0.97 ms−1 Maximal intensity/3.00 ms−1
LIR MIR HIR Walking Sprinting alternate with utility movements (backward running/sideways running) *Abbreviation LIR = low intensity running, MIR = medium intensity running, HIR = high intensity running
2.6
SSP Protocol
This protocol require participants to run between two lines (15 m apart) at various speeds (Fig. 2). The exercises include low and high intensity activities such as walking, low intensity running, medium intensity running, and high intensity running sprinting as well as utility movements (Table 1). At every cycle, participants were required to alternate between sprinting and utility (backward running at the first 7.5 m followed by sideways running). Marker cones were placed at 7.5 m to indicate when participants should change utility movements (see Fig. 2). Sprint speed (kmh−1) were measured in one sprinting direction using 5 Hz GPS unit (with interpolated 10 Hz output). The activities during the SSP were based on spent in each match activity for the U 15 match (Table 1). This SSP does not address differences in playing positions.
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Fig. 2. Schematic representation of the running direction of the soccer simulation protocol (SSP)
3 Statistical Analysis All results are reported as means ± standard deviations. Paired sample t-test was used to determine whether there were any differences in physiological and physical measures between trials. Intra-class correlation coefficients (ICC) were used to determine the relative reliability between trials set of scores. In the ICC, the “two-way random” method was used as suggested by Atkinson and Nevill (1998). The standard error of measurement (SEM) with 95% confidence intervals (95% CI) was furtherpused to assess the reliability. The common method to calculate is SEM = SD ( 1-ICC), however, this only applicable to 68% of population. To make it applicable for 95% of population this formula was used: 95% CI = 1.96 SEM (Atkinson and Nevill 1998). All statistical analyses were performed with SPSS software (version 21.0, SPSS Inc., Chicago, IL) with the level of significance set at p 0.05.
4 Results A summary (means ± standard deviations) of BM loss (kg loss), urine specific gravity (USG), the perceptual scales (RPE, FS, FAS), peak sprint speed (kmh−1), CMJ and HR for both trials are shown in Table 3. Meanwhile, the reliability statistics: Intra-class correlation coefficients (ICC), standard error of measurement (SEM), 95% confidence intervals (95% CI) are presented in Table 4.
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Table 3. Mean and standard deviation for performance and physiological measure in the SSP Measure Trial 1 Trial 2 Mean BM loss (kg) 0.20 ± 0.5 0.24 ± 0.3 0.22 ± 0.4 USG 1.016 ± 0.01 1.017 ± 0.01 1.016 ± 0.01 RPE 12.0 ± 1.4 11.5 ± 1.5 11.7 ± 1.5 FAS 3.2 ± 1.2 3.4 ± 1.3 3.3 ± 1.3 FS 2.6 ± 1.6 2.5 ± 1.7 2.5 ± 1.7 CMJ (cm) 17.5 ± 2 17.4 ± 2 17.4 ± 2 22.2 ± 1.6 22.2 ± 1.8 Peak sprint speed (kmh−1) 22.2 ± 1.9 Heart rate (beatsmin−1) 187 ± 4.9 188 ± 6.2 188 ± 5.5 *Abbreviation: SSP = soccer simulation protocol; BM = body mass; USG = urine specific gravity; RPE = rating perceived of exertion; FAS = felt arousal scale; FS = feeling scale; CMJ = counter movement jump
4.1
Body Mass and Urine Specific Gravity (USG)
Similar amount of BM was lost between trials and hydration status was not different between trials. A paired sample t-test confirmed the results with no significant differences between trials in BM loss (p = 0.740) and USG (p = 0.834) respectively. It was also observed that all participants were well hydrated before trials (1.016 ± 0.01). Table 4. Intra-class correlation coefficients (ICC), standard error of measurement (SEM) and 95% confidence intervals (95% CI) in SSP Variable ICC SEM 95% CI BM Loss 0.87 ±0.1 ±0.2 RPE 0.83 ±0.2 ±0.4 FS 0.85 ±0.2 ±0.4 FAS 0.87 ±0.1 ±0.2 CMJ 0.98 ±0.01 ±0.02 Peak sprint speed 0.87 ±0.1 ±0.2 Heart rate 0.88 ±0.6 ±1.2 Abbreviation: RPE = Rating of perceived exertion; FAS = Felt arousal scale; FS: Feeling scale; CMJ = Counter movement jump * Significant correlation between trials p < 0.05
4.2
Perceptual Scales
The RPE scales showed that the RPE got higher towards the end of the protocol, meanwhile the FAS maintained between 3 and 4 scales while FS showed the feeling dropped towards the end of the exercise (Fig. 3). Nevertheless, the perceptual scales (RPE, FS and FAS) followed a similar pattern of response during both trials with no significant differences in the SSP’s p = 0.835, p = 0.751, p = 0.222 respectively and
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between time points (except in Block 1 for FS). Using ICC confirming relative reliability in the perceptual scales, when there were high correlations between two trials (Table 4). Overall, the results in SEM, 95% CI indicating the repeatability evidence for this protocol.
*
Fig. 3. Mean in the perceptual scales at different time point. No significant differences between trials and between time points in RPE, FAS and FS (p > 0.05). *Significantly difference in Trial 1 and 2 in Block 1 for FS.
4.3
Countermovement Jump
Mean and standard deviation in Table 2 CMJ showed no differences in trial 1 and trial 2 (p = 0.289). Similar to the perceptual scales, no significant differences between time points (Fig. 4) was observed. A significant high correlation was observed in the ICC followed a similar trend in this protocol. The SEM and 95% CI for CMJ were lower in indicating the repeatability between trials. 4.4
Peak Sprint Speed
Fifteen-meter sprint performance deteriorated towards the end of the protocol throughout both trials. No significant differences was observed between time points trials (Fig. 4) in peak sprint speed and between trials (p = 0.933). Similar pattern was observed in peak sprint speed with high correlation in ICC. The SEM in CMJ and peak sprint speed were reported lower and results in 95% CI (Table 4) providing the repeatability of this protocol. 4.5
Heart Rate
The HR increased throughout the exercise in both trials. The mean HR during exercise was higher at the end of blocks in Trial 2 (188 ± 6.5). There were no differences in Trial 1 and Trial 2 (p = 0.333) and between time points (refer Fig. 4). There were high correlations between trials in the (ICC = 0.88).
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Fig. 4. Mean in CMJ, Sprint speed and HR at different time point. No significant differences between trials and between time points in CMJ, Sprint speed and HR (p > 0.05)
5 Discussion The primary aim of this study was to assess the reliability of this new SSP’s for use with young soccer players aged 15 years old incorporates turning movements, speed, jumping, backward and sideways running. This novel study has developed a SSP based on match analysis data. The SSP’s was designed to replicate the total distance covered, duration, match activity patterns and time spent in each match activity pattern observed and physiological demands in typical youth match-play (Table 1). To date, no single simulation protocol was found to be valid and reliable and has been developed directly from match analysis data in young soccer players that cause major limitation to investigate young players. Nonetheless, it is important to note that the total distance of this protocol was adapted by player relative distance covered (m.min−1) because of the rolling substitution policy in youth game and have no relation to positional differences as role of specialization appears to be less important for younger players (Castagna et al. 2003). The findings of this study showed that mean values for kg loss, USG, RPE, FS, FAS, CMJ, peak sprint speed and HR were similar in both trials. We also had monitor these variables throughout the protocols. The data for USG, RPE, FS, FAS, CMJ, peak sprint speed and HR taken at the end of each block showed similar trends in both trials (Fig. 3). Thus, suggesting physiological load is similar between trials and showed this protocol consistently measures whatever is measures. The trend shows HR and RPE progressively increase towards the end of the protocols as expected. However, HR was slightly lower than match and peak sprint speed, which can be justified by no ball
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involvements, attacking or defending movements. Meanwhile, participants typically experience the declined in rating of pleasure-displeasure and arousal scale during prolonged intermittent exercise. In this study, the ICC showed acceptable to excellent correlations. Further assessment for reliability was suggested by Atkinson and Nevill (1998) was SEM and 95% CI. Excellent reliability was measured by small in magnitude in scores between trials. The SEM indicate how the results could change on retesting with the same test. Meanwhile the 95% CI showed the range of “true” scores. The results in this present study showed small values of SEM (±0.01 to ±0.60) and 95% CI (±0.1 to ±1.2) for all variables proved that the protocol is repeatable. This supported by Ali et al. (2014) demonstrated that the SEM in intermittent exercise in adults range from (±4.0 to ±0.6) and 95% CI (±1.3 to ±8.0) indicating excellent reliability between trials. Future studies may use coefficient of variation (CV) to assess the typical percentage error. The CV allows direct comparison of reliability of measures irrespective of calibration or scaling. Thus it facilitates comparison of reliability between ergometers, analysers, tests or populations of volunteers (Hopkins 2000). Moreover, there is no comparison with others as there is no data available for young player’s protocols. This current study had used study by Ali et al. (2014) to estimate sample size. To detect 5% change in total distance covered in LIR, MIR, HIR, walking and sprinting (alternate with utility movements) with power of 0.80, require about 22 participants. The findings from this study have several significant purposes for young athletes, coaching staff or as a research tools. Firstly, This SSP may exposed young soccer players to sufficient stress as in typical soccer match-play. Furthermore, this protocol may be useful to assess athlete readiness following rehabilitation (especially for knees injuries) as this protocol includes turning and changing direction while running. Secondly, at the coaching staff level, this protocol may be used for test battery used in talent identification. These includes intermittent shuttle running such as 20 m progressive shuttle run, repeated sprints and soccer skills such as dribbling, passing and shooting (may be add prior, during and post protocol) which may reduce setting up time for different procedures. In addition, this result of this SSP may be used for coaches to design an effective training programs so that players will be able to get used to the competition loads. Findings from the research may benefit to athletes/coaches to improve on training strategy, preparing specific training programme for young athletes and may help them to improve on soccer skill performances. Researchers may receive the biggest implications from this study. This SSP could be used to investigate young players in various sports science disciplines, mainly in training and nutritional interventions. It is important to highlight that variables that can be identified resulting from supplementation or training intervention are sprint and jumping performance, HR as well as the perceptual scales. Furthermore, adding soccer skills test prior and the end of the protocol may be useful to investigate the effects of nutritional intervention such as CHO-E ingestion. The SSP’s are one of the most extensively used methods to investigate adult players in nutritional interventions (Ali et al. 2007a; Magalhães et al. 2010; Saunders et al. 2012; Sunderland and Nevill 2005). For instance, few studies have used SSP to investigate the effects of ingesting from 6 to 7.5% carbohydrate supplementation in adults soccer players. Main findings shows improvement in shooting performance
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(Ali et al. 2007a), sprinting and jumping performance (Gant et al. 2010), improves intermittent running (Patterson and Gray 2007), improves endurance capacity (Foskett et al. 2008) and soccer skills performance (Currell et al. 2009). Meanwhile, Bishop et al. (1999) investigate the effects of CHO on the immune and plasma cortisol and found minimal influence of CHO in the immune response to exercise. In recent years, consumption of sports drinks or CHO-E beverages has become a common method of replacing fluid, electrolytes and carbohydrate during training and competition in youth players (Care 2011). Examining the effect of a sports drink on a young soccer player is beneficial and may help to answer who question the effectiveness. Few studies have examined the effect of CHO-E supplementation in youth soccer using a modified SSP. Phillips et al. (2010) investigated the effects of 6% CHOE supplementation on endurance capacity and sprint performance in 12-year-old boys during a 60-min intermittent exercise protocol. The results showed a significant improvement in endurance running capacity compared to the placebo trial. Time to fatigue was increased 24.4% and total distance cover was greater in CHO trial. A subsequent study by Phillips et al. (2012) also showed similar improvements on endurance capacity in 13-year-old team game players that ingested 0.818 mL.kg−1 BM of a CHO-E gel followed by 5 mL.kg−1 BM of water 5 min before commencing exercise. Participants consumed 0.327 mL.kg−1 BM followed by 2 mL.kg−1 BM of water during exercise. In both studies, no significant differences in HR, RPE and sprint times. Given the little evidence available, more research is warranted in CHO-E ingestion by using appropriate valid and reliable protocols. It is also important to highlight that both studies were using a protocol (modified Loughborough Intermittent Shuttle Test; LIST, 60 min, 20 m running distance) which was initially designed for adult players who covered 8–12 km during a soccer match. Data from match analysis studies of children’s football suggest that children do not perform an abbreviated version of the running demands of adults (Atan et al. 2014) and thus shortening the LIST may not be appropriate. This was further supported by sprint distance differences between young and adult players. As reported by Atan et al. (2016) the average distance per sprint for 13 to 15 years old player was 16 m, meanwhile adults cover 19.3 ± 3.4 m (Bangsbo et al. 1991). This new SSP offer number of attractive features. Firstly, it can be perform indoors (researchers can control environmental conditions) and outdoors (i.e. natural grass/Astroturf pitch, players can wear their regular soccer footwear). Secondly, peak sprint speeds can be measured either using a sprint gates or GPS. With sprint gates, 1 to 4 participants can be tested simultaneously while GPS offers more accurate data and more participants at a time. Thirdly, limited equipment and tools are required to conduct this test make it accessible to examine players at any playing level (amateur, sub-elite, and elite). For that reason, this SSP provides a practical method that is sufficiently accurate and reliable for assessing young players. We also had included the unorthodox movements such as sideways and backward running to add novelty to this SSP. It was suggested by Nicholas et al. (2000) to include these movements in SSP as sideways and backward running required higher energy expenditure. Young players spent approximately 3% to 4% (Capranica et al. 2010; Nakazawa et al. 2005), in this SSP, the players spent 3.5% in this activity.
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In the present study, the U15 protocol was selected because from U16 they already started playing in 90 min game. Plus, this is the important stage as players has started playing at the elite levels. It is important to note that, this SSP has adapted the LIST, simulation of adult soccer match-play. The LIST has been developed based on the motion analysis data and mimics activities in the match-play and is widely used in soccer research (Nicholas et al. 2000). However, the LIST required the participants performed multistage fitness shuttle run (MSFT) until voluntary exhaustion to deter_ max and running speed (corresponding to 55 and 95% VO2 _ max ). It mine individual VO2 appear that there is no relationship between the cardiovascular fitness and distance covered for the young players therefore running speed in this SSP is fixed based on match speed threshold (Atan et al. 2016). Although it is difficult to simulate every physical demand in soccer, the running activity in this SSP is similar as observed in typical soccer match-play. The running activity pattern is similar as observed in typical soccer match-play including the unorthodox movements such as sideways and backward running which add novelty to this SSP. The differences between match data and the protocol do not exceed 5% which considered within acceptable ranges. Recognising the limitations of this SSP, future studies are recommended to include ball involvements and soccer skills such as Loughborough Soccer Passing test (LSPT) and Loughborough Soccer Shooting Test (LSPT) (Ali et al. 2007b) to enhance the ecological validity of this test. In conclusion, this SSP replicate similar physiological demands and activity patterns that typically observed in U15. With development of SSP’s, it is now possible to investigate youth players in interventions (i.e. training, nutritional), as a tool in talent identification or athlete readiness following rehabilitation. Acknowledgements. The author thank the players from Sekolah Sukan Bukit Jalil (SSBJ) for participating in the study.
References Ali, A., Williams, C., Nicholas, C.W., Foskett, A.: The influence of carbohydrate-electrolyte ingestion on soccer skill performance. Med. Sci. Sports Exerc. 39(11), 1969–1976 (2007a) Ali, A., Williams, C., Hulse, M., Strudwick, A., Reddin, J., Howarth, L., McGregor, S.: Reliability and validity of two tests of soccer skill. J. Sports Sci. 25(13), 1461–1470 (2007b) Ali, A., Foskett, A., Gant, N.: Measuring intermittent exercise performance using shuttle running. J. Sports Sci. 32(7), 601–609 (2014) Alvarado, M.U.: Nutrition for young soccer players. Int. J. Soccer Sci. 3(1), 12–20 (2005) Atan, S.A., Foskett, A., Ali, A.: Special populations?: Issues and considerations in youth soccer match analysis. Int. J. Sports Sci. 4(3), 103–114 (2014) Atan, S.A., Foskett, A., Ali, A.: Motion analysis of match play in New Zealand U13 to U15 agegroup soccer players. J. Strength Cond. Res. 30(9), 2416–2423 (2016) Atkinson, G., Nevill, A.M.: Statistical methods for assessing measurement error (reliability) in variables relevant to sports medicine. Sports Med. 26(4), 217–238 (1998) Bangsbo, J., Nørregaard, L., Thorsø, F.: Activity profile of competition soccer. Can. J. Sport Sci. 16(2), 110–116 (1991)
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Bishop, N.C., Blannin, A.K., Robson, P.J., Walsh, N.P., Gleeson, M.: The effects of carbohydrate supplementation on immune responses to a soccer-specific exercise protocol. J. Sports Sci. 17, 37–41 (1999) Bradley, P.S., Mascio, M.D., Peart, D., Olsen, P., Sheldon, B.: High intensity activity profiles of elite soccer players at different performance levels. J. Strength Cond. Res. 24(9), 2343–2351 (2009) Capranica, L., Tessitore, A., Guidetti, L., Figura, F.: Heart rate and match analysis in prepubescent soccer players. J. Sports Sci. 19(6), 379–384 (2010) Care, R.P.: Sports drinks and energy drinks for children and adolescents: are they appropriate? Pediatrics 127(6), 1182–1189 (2011) Castagna, C., D’Ottavio, S., Abt, G.: Activity profile of young soccer players during. J. Strength Cond. Res. 17(4), 775–780 (2003) Currell, K., Conway, S., Jeukendrup, A.: Carbohydrate ingestion improves performance of a new reliable test of soccer performance. Int. J. Sport Nutr. Exerc. Metab. 19(1), 34–46 (2009) Drust, B., Reilly, T., Cable, N.T.: Physiological responses to laboratory-based soccer-specific intermittent and continuous exercise. J. Sports Sci. 18, 885–892 (2000) Figueiredo, A.J., Gonçalves, C.E., Coelho E Silva, M.J., Malina, R.M.: Characteristics of youth soccer players who drop out, persist or move up. J. Sports Sci. 27(9), 883–891 (2009) Foskett, A., Williams, C., Boobis, L., Tsintzas, K.: Carbohydrate availability and muscle energy metabolism during intermittent running. Med. Sci. Sports Exerc. 40(1), 96–103 (2008) Gant, N., Ali, A., Foskett, A.: The influence of caffeine and carbohydrate coingestion on simulated soccer performance. Int. J. Sport Nutr. Exerc. Metab. 20(3), 191–197 (2010) Hardy, C., Rejeski, W.J.: Not what, but how one feels: the measurement of affect during exercise. J. Sport Exerc. Psychol. 11, 304–317 (1989) Hirose, N.: Relationships among birth-month distribution, skeletal age and anthropometric characteristics in adolescent elite soccer players. J. Sports Sci. 27(11), 1159–1166 (2009) Hopkins, W.G.: Measures of reliability in sports medicine and science. Sports Med. 30(1), 1–15 (2000) Magalhães, J., Rebelo, A., Oliveira, E., Silva, J.R., Marques, F., Ascensão, A.: Impact of Loughborough Intermittent Shuttle Test versus soccer match on physiological, biochemical and neuromuscular parameters. Eur. J. Appl. Physiol. 108(1), 39–48 (2010) Mcgregor, S.J., Nicholas, C.W., Lakomy, H.K.A., Williams, C.: The influence of intermittent high-intensity shuttle running and fluid ingestion on the performance of a soccer skill. J. Sports Sci. 17(11), 895–903 (1999) Nakazawa, M., Ishii, T., Matsuda, S., Kurogi, H., Chikaoka, M., Yamamoto, H.: Analysis of match activities in high school soccer players using a mobile GPS and VTR methods. In: ISBS, pp. 147–150 (2005) Nicholas, C.W., Nuttall, F.E., Williams, C.: The Loughborough Intermittent Shuttle Test: a field test that simulates the activity pattern of soccer. J. Sports Sci. 18(2), 97–104 (2000) Papanikolaou, Z.: Attention in young soccer players: the development of an attentional focus training program. Education 3(1), 1–12 (2011) Phillips, S.M., Turner, A.P., Gray, S., Sanderson, M.F., Sproule, J.: Ingesting a 6% carbohydrateelectrolyte solution improves endurance capacity, but not sprint performance, during intermittent, high-intensity shuttle running in adolescent team games players aged 12–14 years. Eur. J. Appl. Physiol. 109(5), 811–821 (2010) Phillips, S.M., Turner, A.P., Sanderson, M.F., Sproule, J., Ward, S.A.: Carbohydrate gel ingestion significantly improves the intermittent endurance capacity, but not sprint performance, of adolescent team games players during a simulated team games protocol. Eur. J. Appl. Physiol. 112(3), 1133–1141 (2012)
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The Potentiating Effects of an Eccentric Load on Horizontal Jumps Among Handball Players M. N. Muhammad Zulqarnain1,2(&), A. Jasmi1,3, T. Wahidah1, S. M. P. Sharifah Maimunah1, and Adam Linoby1,3 1
Faculty of Sports Science and Recreation, Universiti Teknologi MARA, Seremban, Negeri Sembilan, Malaysia [email protected] 2 Faculty of Educational Studies, UPM, Serdang, Malaysia 3 Sport and Health Sciences, St. Luke’s Campus, University of Exeter, Exeter, UK
Abstract. The objective of this research is to examine the effects of eccentric loading protocol across different time courses using two different conditions (105% repetition maximum and 125% repetition maximum) on a horizontal jump to potentiate activation. Fourteen (n = 14) participants (age 21 ± 1.5; height 171.4 ± 4.8 cm; body mass 65.9 ± 5.4 kg) performed standing broad jump (SBJ) trials on two separate test sessions at least 96 h apart. Each participant needed to undergo baseline (pre) of the jumping and was measured. Next, 105% (105RM) and 125% (125RM) leg presses were performed. After performing the leg press, subjects needed to perform SBJ at 3, 6, 9, and 12 min. The difference in SBJ performance between 105% (105RM) and 125% (125RM) has been analyzed for statistical significance. The statistical significance has been set at p > 0.05. There were significant differences across the time, p = 0.00 (p < 00.5) but no significant differences for both conditions, p = .85 (p > 0.05). However, the highest mean for 105% 1RM improvement was recorded at 6 min (T6 = 2.549) whereby for 125% 1RM, it was found at 3 min (T3 = 2.545) respectively. In conclusion, pre-conditioning loading at 105% 1RM and 125% 1RM is effective in improving SBJ performance at 3 and 6 min after loading. Keywords: Horizontal jump jump (SBJ)
Leg press Eccentric loading Standing broad
1 Introduction Background of Study Post-activation potentiation (PAP) can be specified as a condition where muscle performance is being enhanced suddenly after performing an activity at high intensity [1, 2]. In conjunction with this, the PAP protocol has been implemented in warm-up sessions in order to find the best method to prepare the athletes. Most previous studies that observed PAP as their warm-up protocol used complex training as a tool to potentiate their performance. A complex exercise is a combination of high load training that induces the neuromuscular system and a plyometric exercise in which energy in the same muscle © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 114–122, 2020. https://doi.org/10.1007/978-981-15-3270-2_12
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group is enhanced [3, 4]. Apart from that, PAP is also implemented on different kinds of intensity training to potentiate the optimum effects. Lowery et al. [5] mentioned that the PAP theory has been helpful in showing how muscular performance is improved following a comparatively intense exercise. In a volume-controlled PAP research, the same study showed that a moderate-to-high intensity load of 70% and 93% (1RM) concentrated throughout the entire eccentric-concentric squat cycle results in better jumping performance, with peaked 4 min and 8 min of replacement. PAP’s existing literature have focused particularly on its positive effects in jumping and sprinting on reduced limb kinematics and kinetics [6, 7]. The stimulus is therefore restricted to below one Repetition Maximum (1RM), including in activities such as counter movement jump (CMJ) in which the slightly eccentric element is essential. Other studies concentrated on dynamic (eccentric-concentric) and isometric loading [8, 9]. Several studies have started to examine eccentric contraction because it is sought to generate more torque and force than concentrated and isometric contraction [10–12]. In addition, numerous studies have also shown that the efficacy of concentric eccentric, and isometric strength in the upper body is 40% and 14% more than those obtained through concentric and isometric contractions by elbow flexors, respectively [12]. Piitulainen [13] confirmed that up to 80% more torque is produced eccentrically than concentrically in the same muscle group. Thus, annotated preconditioning appears to involve a larger load in the eccentric phase compared to the focused 1RM. Uncertainty still exists about the relationship between eccentric contraction and increased performance. To the authors’ knowledge, there are lack of studies comparing eccentric PAP using loads above 1RM. It is important to investigate the effects of higher intensity eccentric pre-conditioning on SBJ performance, to bridge the gap in the understanding of the effects of eccentric PAP on subsequent stretch shortening cycle dynamics. Therefore, the purpose of this study is to determine the effects of different intensities of eccentric loading on subsequent SBJ performance through a time course. It is hypothesized that eccentric pre-conditioning at intensities above 1RM would lead to improved subsequent SBJ performance in order to fill the gap in understanding the impacts of the eccentric PAP on continuous jumping performance. It is supposed to lead to better jump results with eccentric pre-conditioning at intensities above 1RM.
2 Method The purpose of the present study is to examine the effects of different eccentric conditioning loads (105RM and 125RM) on consequent SBJ performance, through a time trial (3-min intervals at 3, 6, 9, and 12 min) after an eccentric pre-load. Current study follows a within-subject crossover design where repetitive measures are taken in different eccentric loading circumstances for each participant. Random and balanced testing orders are applied.
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Subjects
Fourteen (n = 14) university handball players were selected as accessible population ranging from 18 to 25 years old who volunteered to participate in this study. All subjects were healthy, physically active, and participated in competition with at least 1year athletic background. Inclusion criteria were as follows: (a) subject was physically active 1 year before the experiment, (b) free from any lower-limb injuries, (c) refrained from any unhealthy dietary habits and did not use any performance-enhancing substances. The sample size was calculated based on the outcome of previous study with mean of difference 122.3 ± 105.7; ES: 1.16 [11]. Thus, a minimum sample size of 10 participants would provide 80% power to detect significant differences of peak power. All procedures were approved by the University Ethics Committee, and participants were provided with an informed consent after the study was approved. 2.2
Procedures
Subjects were requested to complete a familiarization session which consists of standing broad jump (SBJ) exercise and procedure guidance periods of which the 1RM for the leg press was determined in 3 testing sessions over three weeks. During that time, their weight and height were measured—the order in which the testing sessions were done using randomized and counterbalanced design. Then, the subjects warmed up for 5 min. Horizontal jump technique for all subjects at the submaximal stage and maximum effort was carefully performed, familiarized, and standardized. Each participant’s 1RM for the leg press exercise was determined. The formula established for the 1RM leg press used the National Strength and Conditioning Association as the reference [11]. Next, the subjects fulfilled the familiarization and exercised the eccentric loading at 105% and 125% of 1RM at the leg press machine. The order in which the testing sessions were done was randomized and counterbalanced - repeated. The leg press, loaded with chosen weight plates, started in an extended position at a lower limb and descended to a flexed position for 3 s. After the first visit, the individuals were requested to go to the laboratory for at least 96 h of testing after two distinct tests to recover from any delayed onset of muscle soreness from the eccentric load. The tests were linked with two test sessions for 105% (105RM) or 125% (125RM) of 1RM with eccentric loads, followed by four blocks of horizontal jumps at 3 min of a separate trial. 2.3
Measurements
2.3.1 1RM Protocol The test began with three warm-up sets of 5–10 repetitions, followed by 3–5 repetitions, and last 2–3 repetitions consecutively. The 1RM must be fixed with 3–5 repetitions- trials with different loads- and the load increased by approximately 10%–20% until only one repetition was completed effectively. Two minutes of rest were provided to subjects between greater loads along with 4-min time interval within 1RM tests.
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2.3.2 Standing Broad Jumps The subject performed two warm-up SBJs at submaximal effort and a final warm-up SBJ at maximal effort with 30-s rest between jumps. After resting for 2 min, the subject completed two standing broad jumps with maximal effort combined with 1-min recovery. The trial that resulted in the greatest distance was represented as the SBJ’s baseline score. Next, the subject started with their toes on a 0-cm marked line and jumped as far as possible using an arm-swing and landed on both feet. The distance from the back of the heel that was nearest to the 0-cm line was marked and measured. 2.3.3 105% and 125% of 1RM Leg Press The main testing at 105% and 125% load was done for 6 repetitions for 5 s and needed to be finished within a 3-min rest. Then, at an interval of 3 min, 4 blocks of horizontal jump tests were followed. Throughout the course of time, the test included seated rest in between. Eccentric pre-load was implemented in 105RM and 125RM respectively at 105% 1RM 6 repetitions and 125% 1RM 5 repetitions. For both 105RM and 125RM, any other impact needs to be prevented so that the amount of exercise is not interrupted. 2.4
Statistical Analysis
For the purpose of data analysis, the researcher has observed the influences of different intensities of eccentric load on multiple horizontal jumps among handball players throughout the time course given. Two-way repeated measures ANOVA (Statistical Package for the Social Sciences version 22) were used in this study to observe the effects of various intensities of an eccentric load on SBJ across time trial among the handball players. In addition, to examine the temporal changes of the multiple horizontal jump’s performances, 105% and 125% of 1RM of eccentric load and control group were used. This technique involved one group of subjects and would be able to tell if there was a significant difference between the 105% and 125% of an eccentric load.
3 Result Descriptive data and results of statistical analysis for the differences of the measured parameters (repetition maximum, RM) between conditions are presented in Table 1. Means and standard deviation were used for further data analysis. All the outcomes of the results are shown in Table 1 and Fig. 1.
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Table 1. Distance in SBJ throughout the subsequent time course; pre-eccentric and posteccentric time (3 min, 6 min, 9 min, and 12 min) with eccentric load at 105% (105% 1RM) and 125% (125% 1RM) Time
PRE
Intensity SBJ mean ± SD
105RM 125RM 3 min 105RM 125RM 6 min 105RM 125RM 9 min 105RM 125RM 12 min 105RM 125RM
2.504 2.505 2.542 2.545 2.549 2.536 2.474 2.449 2.422 2.368
± ± ± ± ± ± ± ± ± ±
.2187 .1608 .1711 .1618 .1926 .1838 .2023 .1705 .2015 .2261
Comparison between intensities Difference; ±90% CI .1498 ± .1484 .1505 ± .1490 .1329 ± .1258 .1330 ± .1258 .1334 ± .1591 .1334 ± .1591 .1203 ± .1703 .1205 ± .1705 .1128 ± .2199 .1129 ± .2200
p .992 .992 .955 .955 .858 .858 .727 .727 .514 .514
From Table 1, There is a significant difference in main effect for SBJ across the time course with F4,104 = 44.20, p = .005 (p < .005) from pre-eccentric towards the end of 12 min (3 min, 6 min, 9 min, and 12 min) respectively. However, there is no two-way interaction effect between intensity and time with F1,26 = 0.062, p = .805 (p < .005). As for the performance, there is a slight increase from the baseline result up until T6 (6 min), but it slightly decreases after going to T12 (12 min). However, after the posthoc (Bonferroni) adjustment, results have shown that there is a slight difference in SBJ scores particularly at 12 min with p = 0.08. For the 105% 1RM condition, there is an increment in the pre-eccentric condition up to 6 min, but there is a slight decrement from 9 min until 12 min. In contrast, 125% 1RM condition shows an increasing pattern up to 3 min but slightly decreases through 6, 9, and 12 min respectively.
Fig. 1. The figure shows the means between 105% 1RM condition and 125% 1RM condition
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4 Discussion The aim of the current study is to analyze the effects of varying intensities of eccentric pre-conditioning load on consequent performance across the time course after conditioning. The main finding of this study is the effects of different intensities of eccentric loading on horizontal jumps suggest that eccentric pre-conditioning is a compelling PAP to improve the performance of horizontal jumps for both 105% RM and 125% RM. The acute effect of this study can be seen from 3 to 6 min after the eccentric loading. There are four possible mechanisms that lead to this improvement. All the mechanisms suggested are referred from previous studies. The first mechanism is through neural activation increase from the increased stretch of intrafusal muscle fibers resulting from the greater eccentric load [14]. From the great stretch of intrafusal muscle fibers, it will cause a flex arc in a way that there is enhanced inducement of gamma (c) motor neurons that trigger the brain to increase the firing rate of alpha (a) motor neurons leading to the increase in twitch force. In a simple word, the greater the force acting towards our muscle, the more force will be generated. The second mechanism as explained by [15] stated that the increase in the elasticity in parallel and the series of musculotendinous systems lead to an increase in stretchy recoil. The mechanism is related to an elastic band; if more force is being acted towards the rubber, the more force will be generated. The third mechanism is also explained by the same researcher, which stated that the force is generated from the reduction of myofibrillar displacement due to stored elastic energy in fibers at the start of the concentric phase of muscle contraction. The last mechanism is increased pre-loading. From [2], they stated that accentuated eccentric loading allows the agonist muscle to attain a progressive prepared state with a portion of the actin-myosin cross-bridges being attached before concentric action, thus increasing the force production and power output at the early phase of muscle contraction. This mechanism is perhaps the greatest contributor towards the enhancement of subsequent concentric performance from prior eccentric loading [10, 16–18]. The selection of the intensities of current study is based on several previous research. They suggested that intensity of more than 1RM should be between 100% and 130% of 1RM. There are a few studies that used intensity more than 1RM conducted by [10] to investigate bench press performance and by [11] to observe subsequent countermovement jump (CMJ). The selection of intensity is very crucial because it can affect jumping performance either positively or negatively. The selection of the intensity also needs to be done within appropriate planning because unsuitable selection of intensity can lead to injury and decrease in the jumping performance of athletes or subjects. Further study needs to be done for coaches and trainers to determine the best intensity that will give benefits without harming or risking their athletes, at the same time, enhancing their performances. From a recent study, significant effects that improved jumping performance can be observed from 3 min to 6 min after performing the eccentric loading. There were no improvements from 9 min to 12 min which resulted in the decrease of jumping performance. This condition happens due to muscle fatigue and affected by the muscle’s
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contractile history [11, 19, 20]. Our muscle efficiency is influenced by the contractile muscle history. If the muscle activity increases, it leads to a reduction in neuromuscular force, but prior muscular activity can increase the generation of subsequent strength and power. This phenomenon is known as PAP. However, the physiological mechanism of PAP remains unclear. To make the observation, the study on PAP should involve multiple trials. The protocol of this study can be redesigned so that the physiological mechanism on PAP will be made known and give benefits towards future studies and sports industry. A study on the physical condition of the subjects using a technique of serial testing that may influence the results and findings involving recreational athletes showed that they did not respond to PAP [21]. They also found that well-trained athletes showed better force and jumping power compared to recreational athletes. From the findings, eccentric PAP on professional athletes and well-trained athletes may produce an even greater improvement in jumping performance. The method of serial testing used in this study and previous studies also needs to be redesigned as the subsequent trial of horizontal jumps may be affected by the previous horizontal jump that leads to muscle fatigue. Another limitation is the difficulty to adapt to the exercise which affects the results of the horizontal jump. This is because the intensity that has been set is too heavy and needs to be monitored by a spotter and supported by an assistant. Next, this testing has involved very high load and if it is not properly handled, it can cause injury to the subjects. Last but not least, as the leg press machine is limited, this study had to be done in groups and conducted across many different sessions. As a conclusion, PAP can be applied as a training tool for coaches and sports trainers as the findings of this study have shown improvement in jumping performance. The study protocol needs to be redesigned due to the slight decrease of the jumping performance at the later stage of the testing. Most previous studies that observed PAP showed positive and great findings in improving jumping performance. However, there are limited studies that use very high intensity of more than 1 RM of eccentric loading as their testing protocol. Further studies for this intensity can be conducted in the future for the best outcome of application on PAP.
5 Practical Application Results from recent studies clearly show a significant improvement in horizontal jump performance after performing high intensity eccentric pre-conditioning. Coaches and trainers especially for sports that involve explosive and powerful movement can discover the benefits of utilizing eccentric load as a component of their warming up protocol. As mentioned before, very high intensity utilization still needs further observation because there are limited studies that use it as their study protocol. If inappropriate intensity is used, the outcome of the study may lead to a negative effect, which is decrease in athletes’ performance. In addition, this mechanism can be applied within 3 min to 6 min window earlier than the intended activity as most of the previous studies showed great enhancement of jumping performance within the time frame. This sort of training instrument can also be used to enhance efficiency in sport specific testing as pre-evaluation and pre-competition strategies, particularly in areas with
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explosive movement of energy. This study is highly related to fatigue and potentiation effect. Thus, the selection of the protocol should be appropriate especially in precompetition setting. It is important for coaches and sports trainers to understand the differences between fatigue and potentiation effects. Finally, the modification of the training protocol is recommended to determine the best findings of PAP acute responses.
References 1. Naclerio, F., Faigenbaum, A.D., Larumbe-Zabala, E., Ratamess, N.A., Kang, J., Friedman, P., Ross, R.E.: Effectiveness of different postactivation potentiation protocols with and without whole body vibration on jumping performance in college athletes. J. Strength Cond. Res. 28, 232–239 (2014) 2. Aandahl, H.S., Van den Tillaar, R., Von Heimburg, E.: Effect of post-activation potentiation on kinematics and kicking performance in a roundhouse kick with trained martial arts practitioners, pp. 281–284 (2014) 3. Boullosa, D.A., Laurinda, A., Beltrame, L.G.N., Behm, D.: The acute effect of different half squat set configurations on jump potentiation. J. Strength Cond. Res. 27, 2059–2066 (2013) 4. Robbins, D.W., Docherty, D.: Effect of loading on enhancement of power performance over three consecutive trials. J. Strength Cond. Res. 19, 898 (2005) 5. Wilson, J.M.C., Duncan, N.M., Marin, P.J., Brown, L.E., Loenneke, J.P., Wilson, S.M.C., Jo, E., Lowery, R.P., Ugrinowitsch, C.: Meta-analysis of postactivation potentiation and power. J. Strength Cond. Res. 27, 854–859 (2013) 6. Kilduff, L.P., Cunningham, D.J., Owen, N.J., West, D.J., Bracken, R.M., Cook, C.J.: Effect of postactivation potentiation on swimming starts. J. Strength Cond. Res. 25, 2418–2423 (2011) 7. Rahimi, R.: The acute effects of heavy versus light-load squats on sprint performance. Facta Universtatis Fhysical Educ. Sport 5, 163–169 (2007) 8. McBride, J.M., Triplett-McBride, T., Davie, A., Newton, R.U.: The effect of heavy-vs. lightload jump squats on the development of strength, power, and speed. J. Strength Cond. Res. 16, 75–82 (2002) 9. McBride, J.M., Nimphius, S., Erickson, T.M.: The acute effects of heavy-load squats and loaded countermovement jumps on sprint performance. J. Strength Cond. Res. 19, 893 (2005) 10. Cuenca-Fernández, F., Ruiz-Teba, A., López-Contreras, G., Arellano, R.: Effects of 2 types of activation protocols based on postactivation potentiation on 50-M freestyle performance. J. Strength Cond. Res., 1–9 (2018) 11. Ong, J.H., Lim, J., Chong, E., Tan, F.: The effects of eccentric conditioning stimulion subsequent counter-movement jump performance. J. Strength Cond. Res. 30, 747–754 (2016) 12. Stasinopoulos, D., Stasinopoulos, I.: Comparison of effects of eccentric training, eccentricconcentric training, and eccentric-concentric training combined with isometric contraction in the treatment of lateral elbow tendinopathy. J. Hand Ther. 30, 13–19 (2017) 13. Piitulainen, H., Botter, A., Merletti, R., Avela, J.: Multi-channel electromyography during maximal isometric and dynamic contractions. J. Electromyogr. Kinesiol. 23, 302–310 (2013) 14. Poulos, N., Chaouachi, A., Buchheit, M., Slimani, D., Haff, G.G., Newton, R.U., Germain, P.S.: Complex training and countermovement jump performance across multiple sets: effect of back squat intensity. Kinesiology 50, 75–89 (2018)
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15. Esformes, J.I., Bampouras, T.M.: Effect of back squat depth on lower-body postactivation potentiation. J. Strength Cond. Res. 27, 2997–3000 (2013) 16. Cronin, J.B., McNair, P.J., Marshall, R.N.: Magnitude and decay of stretch-induced enhancement of power output. Eur. J. Appl. Physiol. 84, 575–581 (2001) 17. Doan, B.K., Newton, R.U., Marsit, J.L., Triplett-McBride, N.T., Koziris, L.P., Fry, A.C., Kraemer, W.J.: Effects of increased eccentric loading on bench press 1RM. J. Strength Cond. Res. 16, 9–13 (2002) 18. Duthie, G.M., Young, W.B., Aitken, D.A.: The acute effects of heavy loads on jump squat performance: an evaluation of the complex and contrast methods of power development. J. strength Cond. Res. 16, 530 (2002) 19. Oranchuk, D.J., Storey, A.G., Nelson, A.R., Cronin, J.B.: Isometric training and long-term adaptations: effects of muscle length, intensity, and intent: a systematic review. Scand. J. Med. Sci. Sports 29, 484–503 (2019) 20. Petridis, L., Tróznai, Z., Pálinkás, G., Kalabiska, I., Szabó, T.: Modified reactive strength index in adolescent athletes competing in different sports and its relationship with force production. Am. J. Sport. Sci. Med. 5, 21–26 (2017) 21. Fountas, M., Bakaloudi, E., Bassa, E., Xenofontos, A., Kotzamanidis, C.: The effect of highintensity half-squat to the jump performance in recreationally active men. J. Phys. Educ. Sport 12, 310–315 (2012)
The Confirmatory Factor Analysis of the Malay Language Revised Competitive State Anxiety Inventory-2 (CSAI-2R) Among Adolescent Malaysian State Level Athletes Liew Guo Chen1(&) , Hairul Anuar Hashim1, Ngien Siong Chin2 Yee Cheng Kueh3 , and Garry Kuan1,4
3
,
1 Exercise and Sports Science, School of Health Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia [email protected] 2 Physical Education and Health Department, Institute of Teacher Education Batu Lintang Campus, Kuching, Sarawak, Malaysia Unit of Biostatistics and Research Methodology, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia 4 Department of Life Sciences, Brunel University London, Uxbridge, UK
Abstract. The study aims to validate the Malay-language version of the Revised Competitive State Anxiety Inventory-2 (CSAI-2R) using confirmatory factor analysis (CFA). The data were collected from the state level adolescent Malaysian athletes across 21 different sports. A total of 685 athletes participated in the study (males 62%, females 38%), with the mean age of 17.0 (SD = 3.6). A standard forward-backwards translation was performed to translate the 17items CSAI-2R from the original English version. All the participants filled the CSAI-2R Malay version questionnaire. The results of the initial hypothesised model did not show a good fit to the data (RMSEA = .060, CFI = .848, TLI = .822, SRMR = .048). Subsequent model modifications were made by adding correlation among the items’ residuals within the same factor which resulted in good fit indices (RMSEA = .038, CFI = .940, TLI = .926, SRMR = .035). The final measurement model comprised all 17 items of the Malay language CSAI-2R. The internal consistency coefficients measured by Cronbach’s alpha were .741, .619, and .775 for somatic state anxiety, cognitive state anxiety, and self-confidence. Overall, the results indicated that the Malay language CSAI-2R could be used to assess the multidimensional component of the competitive anxiety among adolescent Malaysian state-level athletes. Keywords: Somatic validity
Cognitive Anxiety Self-confidence Factorial
1 Introduction An extensive amount of research has been conducted to investigate the relationship between anxiety and sports performance (Cerin et al. 2000; Jones 1995; Kuan et al. 2018). Anxiety can be multidimensional, and it can be defined as the state of tension © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 123–133, 2020. https://doi.org/10.1007/978-981-15-3270-2_13
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and fear that a person experiences in response to a perceived threat (Martens et al. 1990). The two common forms of anxiety associated with sports are state anxiety and trait anxiety (Spielberger 1966). State anxiety is a less permanent condition of anxiety related to a situation. Trait anxiety, however, is a predisposed personality of an intense feeling of nervousness. In this regard, anxiety is conceptualised as a multidimensional construct with both cognitive (thoughts) and somatic (body) components (Martens et al. 1990). Cognitive anxiety involves worrying about a situation or an upcoming competition, while somatic anxiety is the combination of physical and psychophysiological anxiety typified through various physiological markers such as racing heart rate, shallow breathing or butterflies in the stomach (Gould et al. 2002; Muangnapoe et al. 2016; Woodman and Hardy 2003). Earlier research conducted by Martens et al. (1990) and Raglin (1992) on anxiety based on the unitary phenomenon, often led to a weak relationship and inconsistent findings between anxiety and sport performance. Thus, there is a need to develop a sport-specific and multidimensional inventory to measure both somatic anxiety and cognitive anxiety (Burton 1998). As a result, several different inventories were developed. The Competitive State Anxiety Inventory-2 (CSAI-2) was constructed by Martens et al. (1990), and it has been used extensively in sports studies to measure competition anxiety. Since the introduction of the CSAI-2, the instrument has been considered as a reliable (Burton 1988) and valid instrument (Martens et al. 1990) for measuring the competitive state anxiety. Despite the popularity of the CSAI-2, some studies were concerned about its unstable factor structure. For example, Lane et al. (1999) conducted a CFA on the CSAI-2 using a large sample of different sports athletes with varying levels of competitiveness, and the results indicated that the hypothesised model showed poor fit indices. They suggested that there were some limitations in the three-factor structure as proposed by Martens et al. (1990). Furthermore, a study conducted using the Greek version of CSAI-2R did not demonstrate good support for the original CSAI-2 using the factorial structure (Iosifidou and Doganis 2001; Tsorbatzoudis et al. 1998). Although the Greek studies were limited to relatively small sample sizes, the authors suggested that the Greek version is appropriate to be used as the two-factors measure of anxiety compared to the original version using the three-factor measure (Tsorbatzoudis et al. 2002). Consequently, Lundqvist and Hassmen (2005) suggested that some modifications be made to the original 27 items CSAI-2. Cox et al. (2003) used the Lagrange multiplier test, and they managed to revise the original three-factor measure of the CSAI-2 through a systematic and sequential item deletion. Parameters with an index above 10 were removed in a stepwise fashion, resulting in a 17-item model, which excluded the two somatic items, four cognitive items, and four self-confidence items. The final model displayed an adequate model fit in both the validation and the calibration samples. Thus, the revised CSAI-2R scale showed a better reliable scale compared to the original CSAI-2. After that, CSAI-2R was translated and validated into over 40-different languages such as Swedish (Lundqvist and Hassmen 2005), Spanish (Fernández et al. 2007), Estonish (Raudsepp and Kais 2008), Thai (Panuthai and Vongjaturapat 2009), French (Martinent et al. 2010), Malay (Hashim and Zulkifli 2010; Baghepour and Hashim
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2016), Italian (Letizia et al. 2011), Tunisian (Hajji and Elloumi 2017) and Persian (Baghepour and Hashim 2018). In general, CSAI-2R has shown strong psychometric properties with acceptable model fit indices as demonstrated in diverse languages such as Swedish (NNFI = 92; CFI = .93; RMSEA = .06; Lundqvist and Hassmen 2005), Estonish (CFI = .97 & .96, RMSEA; Raudsepp and Kais 2008), and Thai (Goodness fit index, GFI = .96; NNFI = .99; CFI = .99; RMSEA = .030; Panuthai and Vongjaturapat 2009). Hashim and Zulkifli (2010) validated the Malay version CSAI-2R using a sample of 236 young Malaysian Taekwondo athletes. The CFA results showed a close model fit of the 3-factor CSAI-2R model (v2 = 170.197, df = 116, p < .05; RMR = .06; GFI = .92; RMSEA = .05). Besides, the results revealed marginally acceptable reliability for the three subscales (a = .65 for somatic anxiety, .77 for cognitive anxiety, and .76 for self-confidence). Although the study conducted by Hashim and Zulkifli (2010) provided some support for the psychometric properties of the 17-item version, it was limited due to its sample size and only one sport was involved. In another study, Baghepour and Hashim (2016) observed an excellent model fit in a study involving a larger sample size using CFA and revealed a theoretically meaningful and close model fit on the 3-factor CSAI-2R model (v2 = 223.13, df = 116, df/v 2 = 1.92, CFI = .92, TLI = .91, RMSEA = .05). Despite some indications about the validity and reliability of the CSAI-2R, there is a need to develop this scale further so that it will be able to employs more diverse and more extensive samples. Therefore, this study aims to provide further evidence by investigating the psychometric properties of the Malay language CSAI-2R among the adolescent Malaysian state level athletes from different sports.
2 Methods 2.1
Participants
A total of 685 adolescent athletes who represented various state team in Malaysia, aged between 14 to 21 years old volunteered to participate in this study. The volunteers consisted of 425 males (62%) and 260 females (38%). The participants’ mean age was 17.0 years (SD = 3.6), including Malay (n = 388; 56.6%), Chinese (n = 193; 28.2%), Indian (n = 2; 0.3%), Bumiputera Sabah/Sarawak (n = 94; 13.7%) and others (n = 8; 1.2%). The participants were competed at different levels of competitions from state to International championships. From the sample, 21 types of sports athletes were involved (athletics, n = 99; archery, n = 10; badminton, n = 10; basketball, n = 14; bowling, n = 9; boxing, n = 12; cycling, n = 15; futsal, n = 37; football, n = 98; gimrama, n = 6; handball, n = 4; hoki, n = 15; netball, n = 23; ping pong, n = 3; rugby, n = 3; sepak takraw, n = 2; silat, n = 10; squash, n = 10; taekwondo, n = 10; wushu, n = 14; and volleyball, n = 281). The participants were all Malaysians with a sound understanding of the Malay reading and speaking. Larger samples usually yield more steady results that are more likely to be replicated. In this study, we considered the sample size of 685 to be adequate for conducting CFA analysis of the Malaylanguage CSAI-2R.
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Questionnaire Translation
The CSAI-2R in this study was translated into the Malay language from the original English version by applying the following steps: (1) The original English version was initially translated to the Malay language by one author with the inclination to maintaining content meaning over a word for word literal translation, (2) The translated Malay version was then back-translated to the English language by a local bilingual Malay lecturer, (3) The two final copies were reviewed and finalised by five panels of experts in sport sciences, sport coaching, health psychology, sport psychology and physical educator. The panel members were expert in English and Malay language with over ten years of working experience in their fields of expertise. The panels reviewed the copies by relating each item to its corresponding item in the original English version, and all differences were corrected precisely. Also, the contents were checked to ascertain if they are culturally suitable to the local population. Then, ten athletes were randomly selected to examine the clarity and perception of the final Malay language version. The athletes were asked to respond to the questions. They were also asked to give their view on the contents and the presentation of the questionnaire. The remarks from the volunteers were good, and no modification was needed. 2.3
Data Collection
The data were collected from adolescent athletes who represented a state team for the National Games between April to October 2018. The study was based on a crosssectional design using the self-reported CSAI-2R questionnaire. The questionnaires were distributed to the athletes who had been given an explanation about the purpose of this study. Athletes who would like to volunteer signed the consent form. The participants were then asked to read the questionnaire carefully and respond to each item truthfully. The coaches were briefed about the structure of the questionnaires before it was distributed to the athletes. The estimated time for the completion of the CSAI-2R questionnaire was about 10 min. The instrument was administered in several group sessions, with the researchers present during all the data collection sessions. The questionnaires were checked by the researchers and the coaches upon submission. The first author ensured the completion of all the questions and to minimise any missing data. The athletes were immediately asked to answer the missing data if they were detected. A quick follow-up to review the missing responses minimises the likelihood of missing data occurring (McKnight et al. 2007). A total of 704 CSAI-2R questionnaires were distributed, but at the end of the study, only 685 questionnaires were returned, and all the items were answered. Hence, the final sample was 685 questionnaires, with no missing data. 2.4
Measures
Revised Competitive Sport Anxiety Inventory-2 (CSAI-2R; Cox et al. 2003) The 17 items CSAI-2R inventory was used to assesses the somatic state anxiety (e.g., ‘‘I feel tense in my stomach’’), cognitive state anxiety (e.g., ‘‘I’m concerned that others will be disappointed with my performance’’), and self-confidence (e.g., ‘‘I’m confident
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I can meet the challenge’’) in a competitive setting. It employed a 4-point Likert scale ranging from, “1 = not at all” to “4 = very much so”. The subscale scores were calculated by summing the items in each subscale and then dividing it with the number of items, followed by multiplying it with 10. The ratings ranged between 10–40 for each subscale. Higher scores would indicate higher levels of somatic and cognitive state anxiety or higher levels of self-confidence. 2.5
Ethics Approval
The study received ethical approval from the Universiti Sains Malaysia (USM) Human Research Ethics Committee (USM/JEPeM/18050226) and was conducted following the guidelines of the International Declaration of Helsinki. Prior to the study, the research information sheet was circulated to all the participants. Those who agreed to volunteer signed the consent form and returned the completed CSAI-2R questionnaire to the researchers. The researchers assured the participants about the confidentiality regarding their answers provided in the questionnaire. They were also informed about their right to refuse to redraw from this study without any penalty. All private information was not collected in this study. 2.6
Statistical Analysis
Version 8.0, Mplus was used to analyse the confirmatory factor analysis results. All data were pre-screened, and those questionnaires with missing values were excluded for further analysis. A total of 685 participants completed the CSAI-2R and were included in the final analysis. In this study, we employed MLM estimator for CFA because it is robust to non-normality distribution of data and produce estimates with standard errors, including a mean adjusted chi-square statistic (Muthén and Muthén 1998). Descriptive analysis and Cronbach’s alpha were conducted using the version 25.0 Statistical Package for Social Sciences. The model was initially tested using the maximum likelihood estimation procedure, whereas the evaluation of the goodness of fit indices and construct validity were tested based on the recommendation by Hair et al. (2010). In the present study, the 17 items were based on the 3-factor structure measurement models, following the fit indices to assess the CFA model fit: comparative fit indices (CFI) and Tucker and Lewis index (TLI) with the desired value of over .92; root mean square error of approximation (RMSEA) and standardised root mean square (SRMR) with the desired value of less than .08 (Hair et al. 2010). Furthermore, Wang and Wang (2012) suggested that significant factor loading of .40 and above with modification index was used as a criterion to retain or delete the item from the measurement model. Then, Nunnally and Bernstein (1994) recommended a minimum of .70 as the cut-off point for acceptable Cronbach’s alpha for reliability test.
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3 Results 3.1
Measurement Model CSAI-2R Malay Version
Results of the model tested in this study are presented in Table 1 and Fig. 1. The hypothesised measurement model for CSAI-2R Malay version consists of 17 items and three factors; (1) somatic state anxiety, (2) cognitive state anxiety and (3) selfconfidence. The initial analysis of the hypothesised measurement models provided an unacceptable model fit, as presented in Table 1. Further investigation was made to improve the initial models by adding correlation among items’ residuals within the same factor of somatic state anxiety as displayed in Table 1 and Fig. 1. The results of this revision improved the fit of the data (see Table 1). The final model was accepted without item deletion but adding correlation among items’ residuals within the same factor. Figure 1 shows the standardised item loading of the measurement model. The diagram represented is the final result after adding correlation among items’ residuals within the same factor based on the CFA results and gaining adequate theoretical support. The model demonstrated good factor loading for items 1, 2, 3, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 and 17 (0.40–0.75). However, the values for items 4, 5 and 16 (0.11– 0.34) were below the cut-off point for acceptable factor loading. To maintain the representation of the model, the items were not removed. This is because by removing these items, it would have influenced the theoretical meaning of the construct. Thus, after re-examining the meaning of these items, the authors agreed that the items are suitable for the athletes.
Table 1. Summary for model fit indices Model RMSEA (90%CI) CFI TLI SRMR Model-1 (Initial) 0.060 (0.053, 0.066) 0.848 0.822 0.048 Model-2a 0.038 (0.031, 0.046) 0.940 0.926 0.035 a 1-Factor measurement model with correlated items residual; Q12 and Q6, Q6 and Q4, Q17 and Q15, Q17 and Q12, Q17 and Q6, Q12 and Q4.
3.2
Internal Consistency
Internal consistency coefficients measured by Cronbach’s alpha were .74, .62, and .78 for somatic state anxiety, cognitive state anxiety, and self-confidence. All Cronbach’s a remained steady if any of the items were to be deleted.
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Note. selcon = self-confidence, cog = cognitive anxiety, som = somatic anxiety Fig. 1. The standardised item loading for the measurement model
4 Discussion The development of the Malay language CSAI-2R is a crucial step to determine the athletes’ anxiety among Malay-speaking athletes. The purpose of this study was to determine the psychometric properties of the Malay language CSAI-2R of adolescent Malaysian athletes from different sports using CFA. The original version of CSAI-2R was tested, and it was regarded as valid, reliable, and stable across time based on previous studies (Cox et al. 2003; Terry et al. 2005). Besides, the CSAI-2R was a measure that was regarded as most significant by researches in the field of sport psychology (Ward and Cox 2004). We performed CFA on all the 17 items of the Malay language CSAI-2R to understand how well the 685 adolescent Malaysian athletes fitted into the proposed three-factor structure model. The advantage of using CFA in the factor analysis is that it can be utilised to evaluate the measurement model’s validity with respect to the initial measurement theory. In this study, the results showed low factor loadings for items 4, 5 and 16 (0.34, 0.31 and 0.11 respectively). These three items were “Item 4: My body feels tense”, “Item 5: I am concerned about losing” and “Item 16: I’m confident of coming through under pressure”. After examining the meaning of the items, we decided not to remove the three items from the Malay version of CSAI-2R because deleting those items would affect the theoretical framework of the scale. Moreover, previous studies conducted by Hashim and Zulkifli (2010) had shown good construct validity, and they did not remove the items as well. It was consistent with the theoretical framework of the original CSAI-2R. Experts have agreed that the items are important and they need to remain in the questionnaire. Subsequent investigation of the CFA results had made some recommended modifications by adding correlation among the items’ residuals within the same factor to
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improve the fit of the measurement model in this sample. The final measurement of the re-specified model resulted in a good fit to the data (RMSEA = .038, CFI = .940, TLI = .926, SRMR = .035). The results from the CFA confirmed that the Malay version of CSAI-2R with 17 items represented the three factors with a desirable goodness-of-fit from this large sample of Malaysia adolescent athletes. The finding is also consistent with previous studies conducted by Hashim and Zulkifli (2010), except for the fact that the present sample was larger and more diverse. Hashim and Zulkifli (2010) also reported the three-factor structure of the original English language CSAI2R with all 17 items remained in the final model. The reliability measurement of the Malay language CSAI-2R model was assessed via the internal consistency reliability of Cronbach’s alpha method. This measurement reliability will assess how homogenous the items are in a construct in terms of their variance (Kline 2011). Based on the result, the Cronbach’s alpha was .741 for somatic state anxiety, .619 for cognitive state anxiety, and .775 for self-confidence. The value of the model showed acceptable scale reliability for the construct measured. For Cronbach’s alpha, it should be more than 0.6 or 0.7 for an acceptable internal consistency (Kline 2011; George and Mallery 2003). Some researchers reported that the acceptable values of Cronbach’s alpha should range from .70 to .95 (Bland and Altman 1997; DeVellis 2003; Nunnally and Bernstein 1994). If the Cronbach’s alpha value is too high, it may indicate that some items are redundant as they have the same content but are presented in different guises (Tavakol and Dennick 2011). In the present study, we concluded that the Malay language CSAI-2R had shown acceptable construct reliability of the adolescent Malaysia athletes from different sports based on the value of the Cronbach’s alpha. We acknowledged that there are some limitations to the present study. Firstly, the data were only collected from three states in Malaysia. This may be limited the generalisability of the findings to other populations from different states. A second limitation is the present sample is that the majority of the participants are Malays, which could exhibit prominent ethnic homogeneity. Besides, the sample could also be biased in gender distribution with more male compared to female participants. Another limitation is that the study was conducted with athletes within a broad age range from 14 to 21 years old. Thus, further studies involving other subpopulations, using a narrower age range are warranted to confirm whether the present study is sample-specific or more general. In this study, the Malay language CSAI-2R has shown acceptable indices of internal consistency and factorial validity, which are consistent with the previous studies of the CSAI-2R and can be used to assess the competitive state anxiety and selfconfidence among the Malaysian population.
5 Conclusion The final measurement model for the Malay language CSAI-2R in this study is shown to be a reliable measurement tool for examining the competition state anxiety of the Malaysian adolescent athletes. All the items are retained and are fit for the collected data. The study provides insight into the measurement of competitive state anxiety and self-confidence of the Malaysian population.
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Conventional Jump Warm-Up with and Without Jumping Rope on Jumping Ability Among Volleyball Players Lawrence Balang Bungkong, Nur Khairunisa Abu Talip(&), and Wan Firdaus Wan Chik Universiti Teknologi MARA, Sarawak Branch, 94300 Kota Samarahan, Malaysia [email protected], {nurkhairunisa331, firdaus085}@uitm.edu.my
Abstract. Volleyball is a sport that required the athlete to have a powerful lower limb especially during jumping. The purpose of this study was to investigate the acute effect of warm up with jumping rope versus without jumping rope on leg power among university volleyball players. Sixteen (n = 16) university volleyball athletes range age between 18 to 25 years old. The randomized cross-over design was employed as each of the subject was undergone the no warm-up (NWU), conventional jump warm up with jumping rope (WJR) and warm up without jumping rope (WoJR) that was assessed by Vertical Jump (VJ) test and Standing Broad Jump (SBJ) test with one week of recovery period between the tests to avoid the carry over effect. The data has been analyzed by Statistical Package of Social Science SPSS 22.0. One-way Repeated Measure Analysis of Variance (ANOVA) was employed to observe the effect of NWU, WoJR and WJR on VJ and SBJ among volleyball athletes. The results shown that there is no significant difference between WoJR and WJR on VJ (p = .497), and there was also no significant difference between WoJR and WJR on SBJ (p = .231). However, there was a significant difference measured between of NWU and WoJR on VJ (p = .020). Keywords: Volleyball Conventional jump Jumping rope Without jumping rope Vertical jump and standing broad jump
1 Introduction Volleyball is one of a complex discipline sport consist with high technical, tactical and athletics demand on the player. Volleyball also included the action of spiking or attacking actions. Thus, jumping ability is most needed in this sport which includes for spiking, serving and blocking (Duzgun et al. 2010). In 2010, Makaruk and Sacewicz has stated that jumping rope and the conventional jump can be included as warm-up protocol, as the two variation of warm-up could improve force power performances, force production, peak power and jumping ability. The used of jumping rope is believed to help in the development of tissue elasticity in which, repetitive jumping movement using jumping rope with repeated bouncing will © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 134–141, 2020. https://doi.org/10.1007/978-981-15-3270-2_14
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allow the lower leg adaptation to be more elastic and allows economical energy used in jumping (stores and release more effective). Hence, this will lead to a better consecutive explosive ability and movement (Sipotz and Nelson 2015). Apart from lower leg performance, Duzgun et al. (2010) stated that the use of jumping rope in training may improve the strength of the shoulder external’s rotator and suggested that as the method for shoulder strengthening. This is because the movement of the jumping rope required a shoulder strength to rotate constantly while jumping. Jumping rope has been used widely in the training of some sport for examples boxing, wrestling, tennis and martial arts (Duzgun et al. 2010). Previous researcher suggested an active warm-up for optimizing the performance, as well as warm up that include similar movement to the game or main activity (Makaruk 2013). In previous study by Yamaguchi and Ishii (2005) revealed that the static stretching can lead to the reducing of the knee extensor power and also may reduce the jumping power as compared to using dynamic stretching. Andrejić (2012) on the other hand claimed that warm-up protocol that included dynamic exercises may resulted in the superior performance of the standing broad jump (SBJ) and vertical jump (VJ), which is by only performing the original movement, can improve the performance in jumping. Trecroci et al. (2015) stated that the aim of the rope jump is actually to maintain the constant vertical take-off and landing phases until the end of the exercise. Consequently the jumping that is performed by the athlete of the player will be at the same rhythm from the start to the end of the jump. Periera et al. (2015) stated that, due to the popularity of the volleyball as it become world’s most selected sport, there are many studies that have been conducted regarding to the methods of enhancing performance limited research has been conducted to compare the effects between conventional jump with and without jumping rope for warm-up especially in measuring the jumping ability (Makaruk 2013). Therefore, it is needed to examine the effect of the conventional jump with and without jumping rope in warm up to measure the jumping ability of the VJ and SBJ among university volleyball players.
2 Methods 2.1
Participants
Sixteen (n = 16) male (n = 8) and female (n = 8) volleyball players from Universiti Teknologi MARA (UiTM), Sarawak with age range 18 to 25 years old was recruited for the present study. All athletes must be healthy and free from any injury, highly active in volleyball and represented UiTM, Sarawak Branch for various competition including Kuching Open, Karnival Sukan Mahasiswa UiTM and UNIMAS Open. The participants were divided into two groups with equal numbers of male and female athletes to avoid bias. The mean age of the participants was 22 (SD = 1.67) years old. Mean weight was 59.10 (SD = 1.05) kg and the mean height was 164.94 (SD = 9.86) cm.
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Material
The present study used the VJ and SBJ test to measure the jumping ability. The procedure of the tests was used in the previous study by Changela and Bhatt (2012) and Sue et al. (2017). Both tests were conducted with three trials, with two-minutes rest between trials. Best score was recorded. 2.3
Design
The randomized cross-over study has been used to investigate the jumping performance among the volleyball players. This design is the repeated or longitudinal measurement design. In which all of the subjects was assigned into three (3) warm up protocol which is includes no warm up (NWU) protocol, conventional jump without jumping rope (WoJR) and conventional jump with jumping rope (WJR) protocol and followed by the VJ test and SBJ test. There will be one-week recovery between treatments to avoid the carried over effect. 2.4
Procedures
The study was approved by the Faculty of Sports Science and Recreation UiTM Sarawak’s ethics committee. All participants filled in the consent form and have passed the Physical Activity Readiness Questionnaire (PAR-Q). After that, the subject was briefed about the study. Next, the anthropometry data (includes age, height and weight) was collected. Firstly, all participants had no warm up (NWU group) prior to VJ test and SBJ as a control group. Then, after a week of rest interval, all of the participants performed the warm up protocol WoJR then undergo for the VJ test and SBJ test. After a rest for another one week, the participants performed the warm up protocol WJR then went for the VJ test and SBJ test. The one-week rest period between that three (3) treatments was to avoid the carried over effect to the treatment. Subject also was not allowed to perform any extreme activities throughout the study. The participants were performing the same warm up protocol (with and without jumping rope) (Makaruk 2013); pogo jumps, hip-twist-ankle hop, side-to-side-ankle hop, ankle-flip, jump with high knee, jump with heel kick, fast skipping forward, fast skipping backward.
3 Results The data collected was analysed by Statistical Package of Social Science SPSS 22.0. One-way repeated measure analysis of variance (ANOVA) was employed to measure the effect of conventional jump warm-up with and without rope on VJ and SBJ performance among university volleyball players. Preliminary VJ and SBJ test prior to the intervention was done to measure the normality of the data shown that both skewness and kurtosis of the data was ranged between −2 to +2, which indicated that the data was normal (George and Mallery 2005).
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Findings of the study showed that WoJR warm up protocol produced highest mean on vertical power performance, followed with WJR warm up protocol and NWU protocol (See Fig. 1).
Fig. 1. The mean height of VJ test for NWU protocol is 40.56 cm, WoJR protocol resulted 41.75 cm whereas WJR protocol with 41.5 cm.
On the other hand, WJR warm up protocol produced highest mean on horizontal power performance, followed with WoJR warm up protocol and NWU protocol (See Fig. 2).
Fig. 2. The mean distance of SBJ test for NWU protocol is 219.69 cm, WoJR protocol resulted 226.25 cm whereas WJR protocol with 229.75 cm.
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The pairwise comparison (Table 1) showed that WoJR warm up protocol produced greater vertical jump performance than NWU (p = .02). There was no significant difference showed between WoJR and WJR (p = .497), and between NWU and WJR (p = .144). Whereas the pairwise comparison on SBJ test (Table 2) showed that there was no significant difference on horizontal power between WoJR and WJR (p = .231), between NWU and WoJR (p = .39), and no significant difference between NWU and WJR (p = .201).
Table 1. Effects of warm up protocols to VJ test. Significant difference is set at .05 (p < .05). (I) Factor (J) Factor Mean Diff (I−J) p-value WoJR WJR .25 .497 NWU WoJR −1.188 .020* NWU WJR −.938 .144 *No significant: (p > .05); Significant: (p < .05) Table 2. Effects of warm up protocols to SBJ test. (I) Factor WoJR NWU NWU
(J) Factor Mean Diff (I−J) p-value WJR −3.500 .231 WoJR −10.062 .390 WJR −6.562 .201
4 Discussion The purpose of the study was to examine the acute effect of conventional jump warmup with and without jumping rope on jumping ability among university volleyball players. From the result shown in Fig. 1, WoJR resulted higher than vertical performance as compared to WJR, with 0.58% of differences despite the insignificant difference. It was parallel with the finding by Andrejić (2012) which mention that a warmup protocol that included dynamic exercises mimicking the main activity would have resulted in the superior performance of the long jump and vertical jump. Thus, with and without adding jumping rope, stimulate similar VJ performance, however greater mean in WoJR protocol. In the others finding of the study by Tsolakis and Bogdanis (2012) claimed that by performing the warm up prior to the training and competition, it also may help the athlete to be fully prepared and also to aim the preparation of muscle to attain the maximal power and coordination. Besides, warm up would also increase range of motion of the joint. That mean the warm-up was most beneficial to improve VJ performance. On the other hand, WoJR created significantly better (p = .02) VJ performance as compared to NWU. The pairwise comparisons have shown that WoJR warm up was 2.93% better than NWU. The result proved that by performing warm-up protocol prior to test that included dynamic exercises would significantly have resulted in the superior performance of the VJ. The result of the study was parallel to Andrejić (2012).
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Makaruk (2013) also claimed that warm up that are similar to the exercise can be used to improve plyometric performance especially on the jumping movement. Even though the result between WJR versus NWU on VJ tests shown no significant difference (p > .05), WJR warm up protocol shown a greater jumping performance of VJ (2.32%) as compared to NWU. These result was supported by Trecroci et al. (2015) which stated that the aim of the rope jump is actually to maintaining the constant vertical take-off and landing phases until the end of the exercise. Therefore, the jumping that was performed by the athletes would be at the same rhythm from the start to the end of the jump. This would give the more benefit to the jump that are performed by the athlete. The result of the also has been supported by Sipotz and Nelson (2015) which mentioned that the rope jump is beneficial for the volleyball and the other sport that require a jumping movement, since one of the benefits of the rope jumping is improving the tissue elasticity because of the repeated movement bouncing of the lower leg and may improve in frequency and the effectiveness of jumping. Horizontal power was measured with SBJ test. WJR and WoJR warm up protocols would produce the same results on horizontal power performance (SBJ). However, WJR protocol induced 1.55% greater horizontal power as compared to WoJR protocol. The finding of the present study is supported by Makaruk (2013) which claimed that, using rope jumping as the warm up protocol will improve force power, force production, peak power and jumping ability especially on the horizontal jumping performance. Makaruk (2013) also suggested rope jumping to be included in warm up protocol prior to training or competition as an effective way to improve athlete’s performances. The study also concluded that WoJR warm up and NWU protocols would give insignificant effect on SBJ. Despite the insignificant difference, the mean results in Fig. 2 showed that WoJR protocols induced greater SBJ performance by 2.98% more than NWU. The result of SBJ was similar to VJ, which by performing the warm-up protocol that included dynamic exercises would have resulted in the superior performance of the long jump and vertical jump (Andrejić, 2012). These results also have been supported from the other finding by Cilli et al. (2014). It is claimed that by performing warm up at a moderate to the high intensity of the basis form of sports movement in the training or competition would help to enhance in power generation as well as enhancing performance. Last but not least, the comparison between WJR and NWU on SBJ shown an insignificant difference. WJR protocol however created 4.58% greater horizontal power than NWU protocol. This finding has been supported by Sipotz and Nelson (2015) which claimed that the rope jump will be beneficial for the volleyball and the other sport that require a jumping movement, since one of the benefits of the rope jumping is improving the tissue elasticity because of the repeated movement bouncing of the lower leg and may improve in frequency and the effectiveness of jumping. Apart from that, the rope jumping warm up protocol prior to training or competition would be an effective way to improve athlete’s performances (Makaruk 2013).
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5 Conclusion To conclude, the mean of the present study showed that both WJR and WoJR warming up protocols would have imposed almost similar respond in jumping ability. VJ shown the best result by WoJR protocol, while SBJ shown the best result by WJR protocol. However, NWU protocol resulted poorest jumping ability in both VJ and SBJ test. In VJ, WJR protocol probably increase the complexity of the warm up, thus the athletes were focused on the frequency (step) rather than the height as compared to WoJR protocol. Hence, if the athletes were able to focused on altitude (height) in WoJR, the results of VJ performance would be increase. While in SBJ, WJR created the highest mean as compared to two other protocols. It is probably due to the mechanism of the warm up in WJR protocol that activate more muscle recruitment required in producing greater horizontal power. It would be fascinating for the future study to investigate on this. In the present study, most of the insignificance difference found were probably due to the lack of familiarization of the athletes of the complicated steps of warm up and to jumping rope itself, despite two sessions of familiarization have been implemented prior to data collection. It is recommended for the future study to increase familiarization phase because some of the athlete or participant might be slow in adapting the warm up protocol, as well as to include athletes that is very familiar to rope jumping as the participants. Apart from that, the insignificant results could probably due to the sample size used, therefore it is recommended for the future study to increase the number of sample size.
6 Practical Implication This present study determined the effects of various warm up protocol to be used in training and competition on vertical and horizontal power among volleyball athletes. The findings shown that an appropriate warm up is very important to get the body ready, whereas jumping with or without jumping rope provide similar vertical and horizontal jumping performance. Thus, it is not necessary to include rope jumping as a warm up prior to training or competition, especially when using rope jump is inconvenience.
References Andrejic, O.: An investigation into the effect of different warm-up protocol on flexibility and jumping performance in youth. Phys. Educ. Sport 10(2), 107–114 (2012) Changela, P.K., Sarla, B.: The colleration study of the vertical jump test and wingate cycle test as a method to assess anaerobic power in high scholl basketball players. Int. J. Sci. Res. Publ. 2 (6), 1–6 (2012). ISSN 2250-3153 Cilli, M., Gelen, E., Yildiz, S., Sanglam, T., Camur, M.: Acute effect of resisted dynamic warmup protocols on jumping performance. Biol. Sport. 31(4), 277 (2014)
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Duzgun, I., Baltaci, G., Colakoglu, F., Tunay, V.B., Ozer, D.: The effect of jump-rope training on shoulder isokinetic strength in adolescent volleyball players. J. Sport Rehabil. 2010, 1–16 (2010) George, D., Mallery, P.: SPSS for Windows Step by Step: A Simple Guide and References 12.0 Update, 5th edn. Pearson Education, Boston (2005) Makaruk, H.: Acute effects of rope jumping warm-up on power and jumping ability in track and field athletes. Pol. J. Sport Tourism 2013(20), 200–204 (2013) Pereira, A., Costa, A.M., Santos, P., Figueiredo, T., Jaoa, P.V.: Training strategy of explosive strength in young female volleyball players. Medicina 51(2015), 126–131 (2015) Pescatello, L.S., Arena, R., Riebe, D., Thompson, P.D.: ACSM’s Guideline for Exercise Testing and Prescription. 9 edn. (2013) Sipotz, B., Nelson, D.: The value of jumping rope; bringing back an old staple. In: Mihockeymag, p. 20 (2015) Sue, R.A., Harris, C., Berning, J., Sevene, T., Adams, K.J., Debeliso, M.: Determination of trials needed for measurement consistency of standing long jump in female collegiate volleyball athletes: a brief report. Int. J. Sports Sci. 7(1), 1–5 (2017) Trecroci, A., Cavaggioni, L., Caccia, R., Alberti, G.: Jump rope training: balance and motor coordination in preadolescent soccer players. J. Sports Sci. Med. 14(4), 792 (2015) Tsolakis, C., Bogdanis, G.C.: Acute effect of two different warm up protocols on flexibility and lower limb explosive performance in male and female high level athletes. J. Sports Sci. Med. 2012(11), 669–675 (2012) Yamaguchi, T., Ishii, K.: Effects of static stretching for 30 seconds and dynamic stretching on leg extension power. J. Strength Cond. Res. 19(3), 677–683 (2005)
Identification of Running, Jogging and Walking Activities for Female Athletes Indoor Hockey in 2016 PON Matches Mohammad Faruk(&) , Irmantara Subagio and Heryanto Nur Muhammad
,
Universitas Negeri Surabaya, Lidah Wetan, Surabaya 60213, Indonesia [email protected]
Abstract. This study is aimed to identify running, jogging and walking activities of female athletes in every indoor hockey. It is done by calculating the overall average running, jogging and walking activities for female athletes who compete in three matches. This study is also purposed to determine the distance from each activity of running, jogging and walking so that coaches can get the parameters in preparing the training program. In this study, the researcher considered quantitative research as the design. To collect the data, the researcher utilized a descriptive approach to analyze the video match of the East Java women’s hockey team in the 2016 National multi-event championship. Based on the result, it is explained that the athlete’s average running, jogging and walking activities are 3365.92 m with an average run of 1306.92 m, the average jogging is 535.06 m and the average walking is 523.94 m. The conclusion of this study is the most dominant running activity is 55.24%, while running and walking are almost as big as 22.62% and 22.14%. Keywords: Match analysis
Team sports Indoor hockey
1 Introduction 1.1
A Subsection Sample
Sport is known as a mandatory requirement for every human being because exercising is able to give lots of benefits; physical fitness is one of the examples. Sports begins to expand and are popular with the people at this time starting from children, adolescents, and adults both women and men. In order to improve the training process in sports, several ways and techniques were carried out by observing the competition that had been introduced in recent years. Studying the dynamics of movement and distance traveled by players during matches is a very popular topic for researchers in game sports. This research is very important for better sports preparation from young athletes, because it contributes to the optimization of the physical preparation method. A similar research has been conducted on outdoor hockey [6]. Indoor hockey is known as a discipline that is officially recognized by the International Hockey Federation (FIH). It is proven by special regulations designed for hockey games in which those are different from hockey rules. Placed on the side of the © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 142–147, 2020. https://doi.org/10.1007/978-981-15-3270-2_15
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field as well as unlimited number of substitutes for players, boards make the game quite intense throughout play time. It requires intensive training preparation for the players to achieve dynamic load during the 2 20 min match [1]. In that case, findings on research that focus on running, jogging and walking in a match, the dynamics of movement on the ground and distance traveled will give huge contribution to have more effective and successful planning in the preparation of young athletes. Running is an important activity in which it becomes one of the components in playing hockey. It has such an important role that it helps to increase an athlete’s achievement. Running activity becomes a special concern for coaches because they consider that the players’ running ability contributes to build teamwork in the process of winning a match. High intensity running during matches has proven to be an important differentiator for athletes in elite and sub-elite teams [2]. Previous research has shown that athletes of indoor hockey run for an average of 2900 meters for attackers, 2640 meters for midfielders and 2580 meters for defenders [1] Previous studies of high-intensity game sports (e.g., soccer, field hockey) have resulted in players covering a distance of 9–12 km and sprinting 19–62 min in matches. Nowadays, there are many applications or technologies that support the progress of sports achievements. To find out how far an indoor hockey player runs for a period of 2 20 min, hockey experts usually use statistics to find out the duration. Jogging and Walking are known as important activities in hockey games. It is believed that sufficient recovery will support the performance of athletes in a match. According to the review upon physiological aspect, Jogging and Walking are categorized as the form of recoveries in a indoor hockey match. Considering a very dynamic hockey match that requires fast player movement, it is necessary to adjust the tempo of the game so that athletes can perform with excellent physical condition [1]. I that case, Information on the proportion among running, jogging and walking in an Indoor hockey match am needed for the trainers in preparing the training program so that the training portion will be appropriate and will give positive effect toward the athlete’s performance in the match The purpose of this study is to identify the differences within the activity patterns of indoor hockey women movement during national matches. The identified activities are running, jogging and walking. The information obtained from this research is expected to be useful for coaches in planning training programs and providing insight about the characteristics of activities in matches as a strategy to win a match.
2 Methods 2.1
Participants
To conduct this research, the researcher involved the athletes from the East Java Province Team as the subjects. There are 6 players in the field (2 attackers, 1 midfielder and 2 defensive players), which were observed for 3 matches. The process of collecting the sample is done by using purposive sampling method. In that case, the researcher determines the sample by specifying the characteristics that fit into the purpose of the study. Therefore, it is expected to answer the research problem. The East Java hockey
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team is known as one of the elite teams at the national level. This team became a finalist in the 2015 National Sports Multi-event qualification, and was a champion in an international tournament held in Johor Malaysia in 2016. The researcher chose the East Java Hockey Team as a research subject because it represents the Indonesian national elite team. Thus, it can be used as a parameter for Indoor hockey coaches in Indonesia. In addition, the researcher has obtained permission from the East Java Hockey Coach so that the video recording can be used as the sample of this study. 2.2
Match Analysis
This research was conducted through a detailed observation to get maximum results. The observation was conducted by cutting and separating a video of competition based on the types of activities that had been determined, namely running, jogging and walking. After that the researcher analyzed and calculated the distance by measuring the distance how far the athletes traveled. It was done by comparing the scale of the size on the laptop screen with the size of the field indoor hockey (Fig. 1). The observation was carried out with the duration of the full match in 2 20 min.
Fig. 1. The method of calculating the distance traveled by athletes on video
3 Results Based on data from research results which include walking activities, jogging activities and running activities in female hockey athletes in East Java at PON XIX, West Java: in indoor hockey games, running activity is categorized as an important component that must be considered by both the coach and the player. Running activities plays an important role in the results of a team’s victory, because Indoor Hockey is a sport that requires the athletes to play in a high tempo of game. Thus, it is essential to have technical skills and abilities in high pressure situations of a game.
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Running Activities
The following is a table of results from calculating the distance of running activities for the East Java women’s hockey team (Table 1). Table 1. Table of results of identification of running activities of indoor hockey athletes Round Average of running activities (m) Percentage (%) 54.16 1st-Round 633.24 2nd-Round 673.69 57.62 Full time 1306.92 55.24
Running is an activity that is always used and relied upon both in the process of attacking and defensing and both in dribbling and running without ball. The method of running with maximum effort is usually done with the position of the feet floating in the air and affected by shoulder and head movements [5]. The following is a table of results from calculating the distance of running activities for the East Java women’s hockey team. Based on the results, it can be explained that the average run activity of East Java hockey athletes is 1306.92 m. Then the average running activity in the first round was 633.24 m, while in the second round it was 673.69 m. The running activities of the East Java indoor hockey athletes reached the percentage of 54.16% in the first round while in the second round it increased to the percentage of 57.62% with the total percentage of 55.24%. 3.2
Jogging Activities
The following is a table of result from calculating the distance of jogging activities for the East Java women’s hockey team (Table 2). Table 2. Table of results of identification of jogging activities of indoor hockey athletes Round 1st-Round 2nd-Round Full time
Total of jogging activities (m) 952.25 652.92 1605.17
Average of jogging activities (m) 317.42 217.64 535.06
Percentage (%) 27.15 18.61 22.62
Regarding hockey sports, jogging is an absolute necessity for by hockey athletes. Even jogging activities are not only done in hockey. It is also done in other sports, such as football, futsal, floorball, and others. Jogging is known as a form of running exercise, but it happens at a slower and more relaxed pace. Running is done slowly in order
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to move positions and it is not in a hurry. It aims to keep your shoulders from moving [3]. Based on the results of the research, it is revealed that the total health of jogging activities of East Java hockey athletes is 1605.17 m, with an average of 535.06 m. Then the total jogging activity in the first round is 952.25 m with an average of 317.42 m, while in the second round the jogging activity is 652.92 m with an average of 217.64 m. The jogging activity of East Java hockey athletes is in percentage in of 27.15% during the first round while in the second round jogging activity has decreased to the percentage of 18.61% with the total overall percentage of 22.62%. 3.3
Walking Activities
The following is the table of results from calculating the distance of walking activities for the East Java women’s hockey team (Table 3). Table 3. Table of results of identification of walking activities of indoor hockey athletes Round 1st-Round 2nd-Round Full time
Total of walking activities (m) 655.79 916.04 1571.82
Average of walking activities (m) 218.60 305.35 523.94
Percentage (%) 18.70 26.11 22.15
Walking activity is known as a movement carried out by humans in their daily lives. However, in sports like indoor hockey walking activities are also needed. Indoor hockey sports can not be separated from walking activities for example when athletes play in a high tempo of a game, then walking activities play an important role in these activities. It is done by doing a movement of both feet touching the ground at the same time and doing it like swinging a bicycle [4]. The results of the research on current activities revealed that the total walking activity of East Java hockey athletes is 1571.82 m with an average of 523.94 m. Then the total activity of walking in the first round is as far as 655.79 m with an average of 218.60 m, while in the second round it reaches as far as 916.04 m with an average of 305.35 m. The walking activity of East Java Hockey athletes is at the percentage of 18.70% during the first round. Meanwhile, in the second round it has increased at the percentage of 26.11% with the total overall percentage of 22.15%.
4 Conclusion Based on the research that has been conducted through observing a video of indoor hockey competition by analyzing the running activities of East Java hockey female athletes, it can be concluded that there are three components of physical activities including running activity, jogging activity and walking activity. Based on the results
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of the study, it is known that running is at the percentage of 55.24%, while jogging and walking were at the percentage of 22.62% and 22.14%. The conclusion of this study is that apparently the activity of running is more dominant among the other activities. Based on the total physical activity, it is obvious that running activity and walking activity increased in the second half. However, it decreased in the second half for jogging activity.
References 1. Dimitrieska, T.: Characteristics of 16-year-old Hockey players running activity during an indoor Hockey game. J. Activit. Phys. Educ. Sport 4(2), 142–144 (2014) 2. Gabbett, T.J.: GPS analysis of elite women’s field hockey training and competition. J. Strength Cond. Res. 24(5), 1321–1324 (2010) 3. Konarksi, J.: Characteristics of chosen parameters of external and internal loads in eastern European high level field hockey players. J. Hum. Sport Exerc. 5(1), 43–58 (2010) 4. Konarksi, J., et al.: Different team defense tactics and heart rate during a field hockey match. J. Stud. Phys. Cult. Tour. 27, 145–147 (2006) 5. Lythe, J.: A thesis submitted to the Auckland University of Technology in fulfilment of the degree of Masters of Health Science. The Physical Demands of Elite Men’s Field Hockey and the Effects of Differing Substitution Methods On the Physical and Technical Outputs of Strikers During Match Play (2008) 6. Rechichi, C., Polglaze, T., Spencer, M.: Physiological Tests for Elite Athletes, 2nd edn. Human Kinetics, Australia (2013)
Carbohydrate Mouth Rinsing in Thermoneutral Enhances Prolonged Running Performance Compared to Hot-Humid Environment Harris Kamal Kamaruddin1,2(&), Cheong Hwa Ooi2, and Ahmad Munir Che Muhamed2 1
Faculty of Sports Science and Recreation, Universiti Teknologi MARA, Perlis Branch, 02600 Arau, Perlis, Malaysia [email protected] 2 Advance Medical and Dental Institute, Universiti Sains Malaysia, Gelugor, Malaysia
Abstract. Rinsing with carbohydrate (CHO) has been shown to provided ergogenic benefits on exercise performance of duration up to 1 h. However, the effect of CHO mouth rinsing within varying environmental conditions remains indistinct. The objective of the study was to investigate the effect of CHO mouth rinsing the effects of CHO mouth rinse on time to exhaustion (TTE) running performance in thermoneutral (TN) and hot-humid (HH) environment. Twelve well- trained male endurance runners (mean ± SD; age: 25 ± 3 years; body fat: 7.8 ± 1.8%; VO2peak: 59.8 ± 4.0 mL kg−1 min−1) performed steady-state running exercise at speed eliciting 70% of VO2peak until exhaustion. In a doubleblind, randomised cross over design, two of the trials were conducted in a TN (20 °C, 40% RH) with another two in a HH (30 °C, 70% RH) environment. Each of the runners rinsed their mouth with either a 6% CHO solution, or a taste matched placebo (PLA) solution intermittently during exercise. A significant main effect of environment (TN vs. HH; p < 0.001) on running performance and a significant effect on treatment was detected (CHO vs. PLA; p < 0.001) however, no interaction effect between the 2 variables (p = 0.197). CHO mouth rinse improves TTE in TN compared to HH environment (80.2 vs 53.2 min; p < 0.001). A significantly higher heart rate, oxygen consumption, rectal temperature, skin temperature, and body temperature were recorded in the HH compared to the TN trials (p < 0.05). The psychological scale of arousal level and perceived rating exertion showed a significant difference in TN compared to HH trials (p < 0.05) but not for gastrointestinal comfort and mood state (p > 0.05). There was no difference between plasma glucose or lactate between trials (p > 0.05). These data demonstrated that distinct influence of the environmental condition on the efficacy of CHO mouth rinsing and endurance running exercise performance. The increased in cardiovascular and physiological strain during the exhaustive running exercise observed in a heat environment were the key reasons for decreased exercise performance when compared to a cooler environment. Keywords: Dextrose
Oral wash Heat Endurance Running
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1 Introduction Carbohydrate (CHO) mouth rinsing has been shown to improved exercise performance with high intensity exercise (*70% VO2max) with up to 1 h exercise duration (Dolan et al. 2017; Fraga et al. 2015; Rollo et al. 2015). Several studies have shown an enhancement in endurance exercise performance within temperate condition (19 °C– 22 °C and 45%–60% relative humidity; RH) (Carter et al. 2004a, b; Clarke et al. 2017; Fraga et al. 2015; Rollo et al. 2010) and in a heat stress environment (30 °C–35 °C and 60%–75% RH) (Che Muhamed et al. 2014; Cramer et al. 2015; Watson et al. 2014). It has been suggested the improved exercise performance may due to the non-metabolic effects, with no changes in the blood glucose level or substrate availability (Carter et al. 2004a, b). With that, the effectiveness of CHO mouth rinsing was associated with greater brain activation through oral sensory receptors that influence exercise performance (Chambers et al. 2009). The belief that dehydration harms aerobic exercise performance remains controversial over the last decade with studies supporting (Cheung et al. 2015; Wall et al. 2015; Yamashita et al.2015) as well as rejecting it (Bardis et al. 2013; Maughan 2003; Montain and Coyle 1992). Studies have reported that dehydration did not pose any serious effects to exercise performance in heat stress condition, where the level of the body water loss a 2% of dehydration (Cheung et al. 2015; Wall et al. 2015; Yamashita et al. 2015). A recent study demonstrated that hydration level during exercise had a distinct influenced on the effectiveness of CHO mouth rinsing were dehydrated subjects had improved exercise performance in larger magnitude compared to well-hydrated subjects (Kamaruddin et al. 2017; Kamaruddin et al. 2019). Prior to this study, the CHO mouth rinsing shown to have no ergogenic benefits during exercise in heat stress environment (Che Muhamed et al. 2014; Cramer et al. 2015; Watson et al. 2014). Since any intervention that influences rating perceived exertion (RPE) can change exercise performance, the responses through CHO mouth rinsing may be reduced in an adverse effect of environmental condition. Definitely, the increased level of thermoregulatory responses (core and skin temperature) concomitant with attainment cardiovascular strain, is a major limitation to exercise performance in the heat (Ely et al. 2010; Periard et al. 2011). Exercise in a heat stress environment, demand redistribution of cardiac output with greater skin blood flow (SkBF) (GonzalezAlonso et al. 2007; Rowell et al. 1966), without conceding oxygen delivery to working muscle (Gonzalez-Alonso et al. 2008). Arngrimsson and colleagues (2003) revealed that the increased heart rate (HR) during exercise in heat stress environment demanded a relatively higher percentage of maximal oxygen uptake utilization due to a decreased in maximal oxygen uptake, resulting in greater exercise intensity at any exercise intensity (Gonzalez-Alonso and Calbet 2003; Wingo et al. 2005). Consequently, during selfpaced exercise in a heat stress environment, an elevated Tsk and cardiovascular strain reduced exercise performance (Tatterson et al. 2000), while perceived exertion remains comparable or is impaired (Tucker 2009) when compared to exercise performed in more less thermal strain conditions (Periard and Racinais 2015).
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While benefits of CHO mouth rising has previously been studied in both temperate and heat stress environment separately, there has not been a systematic study that had compared the ergogenic benefit of CHO mouth rinsing in a single study among a homogenous population of well-trained endurance athletes, such as runners. Most data have indicated performance improvement of 1.8% to 11.6% enhancement with CHO mouth rinsing conducted in thermoneutral (Jeukendrup et al. 2013) whereas inconclusive for the heat stress environment (Che Muhamed et al. 2014; Cramer et al. 2015; Watson et al. 2014). To date, there is a lack of understanding of the influence of the environmental condition on the effectiveness of CHO mouth rinsing on endurance running performance. Therefore, this study aimed to examine the influence the environmental condition on time to exhaustion (TTE) of running performance across a thermoneutral (TN) and a hot-humid (HH) environmental condition while performing mouth rinsing with a carbohydrate (CHO) and a placebo (PLA) solution. It was hypothesized that the environmental condition of TN and HH environment would have an impact on the effectiveness of CHO mouth rinsing.
2 Materials and Method Subjects A 12 well trained male endurance runners (age 25 ± 3 y; stature 170 ± 4.5 cm; body mass 58.4 ± 3.6 kg; maximal aerobic power (or VO2peak) 59.4 ± 4.0 mL.kg−1.min−1, training log; 85.5 ± 21.0 km per week; 5 ± 1 days per week) participated in this study. Upon engaging the experiment protocol, all subjects were engaged with medical check-up, health screening and sign a consent form. All subjects were brief with the experimental protocol; however, the true objective of the study remained untold until all subjects have completed the trials. An interview with the subjects revealed that none of them practised mouth rinsing and aware of the ergogenic benefits of CHO mouth rinsing. This study was approved from the Human Ethics Committee of Universiti Sains Malaysia (USM/JEPeM/15070254) and conformed to the latest version of the Declaration of Helsinki. Table 1 presents the descriptive characteristics of the selected subjects.
Table 1. Characteristics of the selected participants Parameters Mean ± SD; (n = 12) Age (y) 25 ± 3 Body mass (kg) 58.5 ± 3.6 Height (cm) 170.0 ± 4.5 VO2peak (mL kg.min−1) 59.8 ± 4.0 BMI 20.1 ± 1.5 Percentage of body fat (%) 7.8 ± 1.8 Training volume (km.week−1) 85.5 ± 21.0 Note. Values are presented as mean ± SD.
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Experimental Design All subjects were required to engage with five experimental visits. The first visit was a preliminary testing and familiarisation sessions, where the subject’s VO2peak were determined, and submaximal running speed was calculated. The subsequent four visits were experiment trials of either in 2 in the TN environment (20 °C and 40% RH) time to exhaustion (TTE) running exercise with CHO or placebo (PLA) (i.e., TN-CHO and TN-PLA, respectively) or 2 in the hot humid (HH) environment (30 °C and 70% RH). All experiment was conducted in counterbalance, randomise and double-blind trials, with 7 days of washout period between trials. The experiment protocol starts at 8:00 am after an overnight fast, where each subject performed an experiment session that consisted of exercise-induced dehydration phase (EID), rest phase and TTE exercise phase. A 25 ml of either CHO or PLA were given intermittently during the TTE and split into a beaker for later weight. Dietary intake for each subject was recorded to ensure similar glycogen concentrations to each experimental trial and was asked to replicate them in the day prior to the subsequent experimental trials. Prior to 24 h before each experimental trial, subjects were asked to avoid any strenuous physical activity, alcohol and caffeine consumptions. The schematic diagram of the experimental protocol is presented in Fig. 1. a. Preliminary testing and familiarisation A running economy running and graded maximal exercise test was performed on a motorized treadmill (HP Cosmos, Nussdorf, Germany) to measure each subject maximal oxygen consumption (VO2peak). A metabolic cart (TrueOne 2400, Parvomedics, Utah, USA) was used to sample respiratory gases (oxygen uptake, VO2, and carbon dioxide, VCO2) and heart rate (HR) was monitored throughout the test. The estimated running speed for each subject was calculated using a linear regression line and plotted between submaximal VO2 and treadmill velocity which equivalent to 60% and 70% VO2peak which had been applied for their exerciseinduced dehydration and TTE runs, respectively. Subjects then were familiarised with all testing protocol and mouth rinsing procedure whilst performing the running exercise on a treadmill.
Fig. 1. Representation diagram of the experimental protocol. Exh; exhaustion; CHO: carbohydrate; PLA: placebo; TN: thermoneutral; HH: hot-humid.
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b. Exercise-induced dehydration (EID) phase During the arrival, pre-exercise body mass was collected (Mettler Toledo, Ohio USA) and urine specific gravity (USG) (Atago Co. Ltd, PAL-10 s, Tokyo) was determined. The EID phase consisted of 30 min running at 60% of VO2peak and continue another 30 min of passive heating in an environmental chamber pre-set at 35 °C and 70% RH. Thereafter, post body mass and USG were collected to determine body fluid loss and hydration status. The EID protocol induced a 2.09% ± 0.21 body mass deficit of the subjects. c. Rest phase After the EID phase, subjects were usher to air condition room (22 °C and 40% RH) for rest (60 min). During this phase, subjects were given a standardized breakfast (2.5 g.kg−1 of their body mass), which consisted of high CHO food such as cereals and bread (Lane et al. 2013) and a minimal 50 ml of plain water to ensure each subject remained dehydrated. Approaching the end of the resting phase, the USG of the subjects was measured. The USG value that reflected hydration level was labelled as well hydrated (1.030) (Casa et al. 2000). d. Time to exhaustion (TTE) test After the rest phase, the subjects executed the TTE running with speed equivalent to 70% of their VO2peak until volitional exhaustion in an environmental chamber preset at a TN condition (20 ± 0.4 °C and 40 ± 4% RH) or HH environment (30 ± 0.2 °C and 70 ± 6% RH). All performance, physiological and psychological variables were remained concealed to the subjects. Respiratory gases and physiological measures (i.e., oxygen consumption (VO2) perceived exhaustion (RPE), perceived arousal, gastrointestinal (GI) comfort) were collected at pre-exercise ad 15 min interval. Heart rate, rectal temperature (Tre) and skin temperature (Tsk) were continuously monitored during the run. The mean Tsk was collected using temperature sensor (iButton, Maxim Integrated Products, Sunnyvale, CA., USA) from 4 sited left shoulder, left chest, right mid-tight and right mid-shin) (Ramanathan 1964). At the exhaustion of the TTE run, the subjects dismantle all clothing and instrumentation, towel-dried and post-exercise body mass and USG were collected. Solution and Mouth Rinsing Protocol The mouth rinse solutions consisted of 6% dextrose (Sim Company, Penang, Malaysia), and the PLA was a taste-matched of commercially available artificial sweeteners (Sucralose, Diabetasol, Jakarta, Indonesia). Each mouth rinse consisted of 25 ml of solution, swirled for 10 s and expectorated into a beaker for weighing weighed (Tanita KD-160, Tokyo, Japan). Each solution was prepared freshly and was kept at 15 ± 0.2 °C. The mouth rinsing was given at 15 min interval during the TTE run (Fig. 1), and they were duly informed of the solutions given to them until the accomplishment of the study.
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Blood Sample and Analysis A 4 mL of the blood sample was obtained from radial vein intermittently (at every 15 min) during the TTE running test via an inserted catheter (22G Surflo Terumo Med Corporation, Eklton, MD., USA) for plasma glucose and lactate determination. After each blood sample is drawn, the catheter was flushed with 2–3 mL of saline (0.9%) (BBraun, Malaysia) to ensure the patency of the vein. All drawn blood sample was kept in a vacutainer containing sodium fluoride/potassium oxalate (BD Vacutainer, Lakes USA) and centrifuged at 3500 rpm for 5 min (Kamaruddin et al. 2019). The plasma was extracted and kept in a secure tube and store at −80 °C for further analysis. The plasma glucose was determined using UV spectrophotometer (Optima SP-3000 Plus, Tokyo, Japan) with commercial buffer kits (Randox, Daytona, UK), while plasma lactate were analyses using electro-enzymatic method (YSI 1500 Sport, Yellow Spring, Ohio, USA). Psychological Measure The subject’s perceived psychological measures were recorded intermittently (at every 15 min) during the TTE running test. The scale consisted of rating perceived exertion (RPE), perceived activation scale (FAS) (Svebak and Murgatroyd 1985), feeling scale (FS) (Hardy and Rejeski 1989) and gastrointestinal scale (GI)) (Rollo and Williams 2010). A perceived thirst was recorded using a visual analogue scale (VAS) with anchor point was labelled “not thirsty” at 0 mm mark and “very thirsty” at 100 mm mark. Statistical Analysis The sample size was determined by using previously reported differences in arousal scale (FAS) (Rollo et al. 2015) with significant difference tailed a = 0.05 and 1 −b = 0.80 (Dupont and Plummer 1990). All data were analysed using SPSS (ver. 24.0, Chicago IL) and presented as mean ± SD. All data were analysed using Statistical Package for Social Science (SPSS, ver. 24.0, Chicago IL) are presented as mean ± SD. The main effects of the environment and mouth rinsing solutions were analysed using two-way ANOVA with a repeated measure, to search for any significant main effects or interaction effects. Mauchly’s test of sphericity was applied, and if sphericity was violated, the Huynh-Feldt estimate was used to correct the data. Also, a repeated measure ANOVA was used to examine mean data between trials (e.g. USG, perceived thirst, HR, Tre, Tsk, etc.). If a significant were detected, post-hoc paired t-test, using Holm-Bonferroni adjustment, were performed. Moreover, partial eta squared (g2p ) and Cohen’s d effect size estimation were calculated, which were defined as trivial (0– 0.19), small (0.20–0.49), moderate (0.50–0.79) or large (>0.80) (Cohen 1992).
3 Results Hydration Status The body mass and percentage of mass loss were presented in Table 2. The post-EID body mass was 58.37 ± 3.47, 58.99 ± 4.39, 58.52 ± 3.70 and 58.93 ± 4.21 kg for TN-CHO, HH-CHO, TN-PLA and HH-PLA trials, respectively. Post-EID phase indicating a hypohydration status of 2.08 ± 0.11, 2.14 ± 0.18, 2.04 ± 0.15 and
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2.08 ± 0.17% body mass differences for TN-CHO, HH-CHO, TN-PLA and HH-PLA trials, respectively. The USG data shown all subjects at all trials were at dehydrated state before the TTE; however, the USG data showed similarities between all trials (p > 0.05). Post-TTE phase, body mass was further decreased from pre-TTE phase; 55.89 ± 3.45, 56.62 ± 4.25, 55.59 ± 3.62 and 56.70 ± 4.05 kg for TN-CHO, HHCHO, TN-PLA and HH-PLA trials, respectively. However, post hoc multiple comparison analysis shows that there was no significant difference in body mass between trials at any phases of the experiment trials (p > 0.001). Table 2. Body mass, urine specific gravity (USG) and body mass deficit measured at various phases of the experiment. EID, exercise-induced dehydration; TTE, time to exhaustion. Variable Body mass (kg)
Changes in body mass (%) Urine specific gravity (USG)
Trial TN-CHO HH-CHO TN-PLA HH-PLA TN-CHO HH-CHO TN-PLA HH-PLA TN-CHO HH-CHO TN-PLA HH-PLA
Pre EID 58.53 ± 58.99 ± 58.52 ± 58.93 ±
1.016 1.013 1.015 1.013
± ± ± ±
3.47 4.39 3.70 4.21
0.008 0.010 0.007 0.008
Post EID 57.32 ± 3.42† 57.73 ± 4.33† 57.33 ± 3.66† 57.71 ± 4.06† −2.08 ± 0.11 −2.14 ± 0.18 −2.04 ± 0.15 −2.08 ± 0.17 1.017 ± 0.006 1.012 ± 0.008 1.015 ± 0.008 1.014 ± 0.008
Pre TTE 57.33 ± 3.42 57.76 ± 4.33 57.31 ± 3.55 57.71 ± 4.12 −2.06 ± 0.68 −2.09 ± 0.24 −2.06 ± 0.25 −2.08 ± 0.15 1.025 ± 0.003* 1.025 ± 0.002* 1.026 ± 0.002* 1.025 ± 0.003*
Post TTE 55.89 ± 3.45†# 56.62 ± 4.25†# 55.59 ± 3.62†# 56.70 ± 4.05†# −4.52 ± 0.74 −4.01 ± 0.58 −4.38 ± 0.32 −3.79 ± 0.58 1.029 ± 0.002*# 1.027 ± 0.002*# 1.029 ± 0.002*# 1.027 ± 0.002*#
Note. Values are presented as mean ± SD. †Significant difference between previous phase (p < 0.001), *Significant difference between previous phase (p < 0.05), #Significance effect of time. TN: thermoneutral, HH: hot-humid; CHO: carbohydrate; PLA: placebo.
Time to Exhaustion and Distance Covered The time to exhaustion were 80.2 ± 4.0, 54.7 ± 5.4, 76.2 ± 3.8 and 54.4 ± 5.1 min for TN-CHO, HH-CHO, TN-PLA and HH-PLA, respectively (Fig. 2A). There was no trial order effect for all trials during the TTE exercise running performance investigation (p = 0.79). Statistical analysis revealed that a significant main effect on environment (F = 22.4, df = 1, p < 0.001, g2p ¼ 0:67) and solutions mouth rinsing (F = 171.5, df = 1, p < 0.001, g2p ¼ 0:94) however no interaction effect between environment-solutions mouth rinsing were detected (F = 4.27, df = 1, p = 0.63, g2p ¼ 0:28). Post hoc analysis revealed that there was significant difference in time performance for TN-CHO when compared to TN-PLA trial with a 4.1 ± 3.0 min improvement (or 5.0 ± 3.8%; p = 0.005) and compared to with HH-CHO trial with a
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25.5 ± 6.9 min improvement (or 31.7 ± 7.6%; p < 0.001). Similarly, there was a significant difference between TN-PLA with HH-PLA trial with a 22.1 ± 6.4 min improvement (or 28.7 ± 7.6%; p < 0.001) with no significant difference between HHCHO with HH-PLA trial (p = 1.000). The mean distance covered was 16078 ± 2210, 10241 ± 1743, 15178 ± 2014 and 10150 ± 1535 m for TN-CHO, HH-CHO, TNPLA and HH-PLA, respectively (Fig. 2B). There was a significant distance coved between TN-CHO with HH-CHO and between HH-CHO trials (p < 0.001), respectively. Similarly, a significant difference between TN-PLA with HH-PLA trial (p < 0.001). However, no significant difference between HH-CHO with HH-PLA trial (p = 1.000).
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Cardiorespiratory Response There was a significant main effect on environment for VO2 (F = 0.29, df = 3, p < 0.001, g2p ¼ 0:99), however no significant effect of CHO mouth rinsing (F = 171.5, df = 1, p = 0.73, g2p ¼ 0:01) and no interaction effect between environment-CHO mouth rinsing were detected (F = 0.39, df = 3, p = 0.61, g2p ¼ 0:01) (Fig. 3A). Post hoc multiple comparison analysis showed that there was a significant difference for VO2 among the trials (F = 8.88, df = 4, p < 0.001, g2p ¼ 0:38). There was a significant difference between TN compared to HH trials (CHO vs PLA) at the 15 to 45 min during the exercise (p < 0.05), respectively. Similarly, there was a significant main effect on environment for HR (F = 6.10, df = 2, p = 0.005, g2p ¼ 0:12), however no significant effect of CHO mouth rinsing (F = 0.77, df = 2, p = 0.90 g2p ¼ 0:002) and no interaction effect between environment-CHO mouth rinsing were detected (F = 0.12, df = 2, p = 0.86, g2p ¼ 0:003) (Fig. 3B). The HR was shown significant difference between TN compared to HH trials (CHO vs PLA) at the 20 min to the exhaustion (p < 0.05), respectively. Metabolic Variables There was a significant effect of time for plasma glucose and lactate (p < 0.05) (Table 3). However, statistical analysis revealed that no significant main effect on the environment, CHO mouth rinsing or any interaction effect between environment-CHO mouth rinsing was detected for both plasma glucose and lactate (p > 0.05), respectively.
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Table 3. Plasma glucose and lactate concentration (mmol.L−1) of time to exhaustion for TNCHO, HH-CHO, TN-PLA and HH-PLA at 0 min and at every 15 min interval during TTE. Exh, exhaustion; min, minute. Time to exhaustion 0 min 15 min 30 min 45 min End Plasma glucose (mmol.L−1) TN-CHO trial 3.4 ± 0.6 4.5 ± 0.3 5.1 ± 0.5 5.4 ± 0.5 5.6 ± 0.4# HH-CHO trial 4.0 ± 0.8 4.7 ± 0.8 5.7 ± 0.4 5.7 ± 0.6 5.8 ± 0.6# TN-PLA trial 3.5 ± 0.7 4.5 ± 0.6 5.3 ± 0.5 5.3 ± 0.7 5.6 ± 0.5# HH-PLA trial 4.1 ± 0.6 4.7 ± 0.6 5.7 ± 0.6 5.7 ± 0.7 6.0 ± 0.5# Plasma lactate (mmol.L−1) TN-CHO trial 1.8 ± 03 3.3 ± 0.8 4.3 ± 0.8 4.7 ± 1.0 5.7 ± 1.1# HH-CHO trial 2.0 ± 0.2 3.6 ± 0.8 4.4 ± 0.7 4.9 ± 0.6 5.4 ± 0.4# TN-PLA trial 1.7 ± 0.3 3.2 ± 0.6 4.0 ± 0.9 4.4 ± 0.8 5.2 ± 0.5# HH-PLA trial 2.0 ± 0.1 3.7 ± 0.6 4.5 ± 0.6 4.9 ± 0.6 5.3 ± 0.5# Note. Values are presented as mean ± SD. #Significant effect of time. TN: thermoneutral; HH: hot-humid; CHO: carbohydrate; PLA: placebo
Thermoregulatory Response The mean Tre showed a significant main effect on environment (F = 10.9, df = 3, p < 0.001, g2p ¼ 0:20), however no significant effect of CHO mouth rinsing (F = 0.36, df = 3, p = 0.81, g2p ¼ 0:01 and no interaction effect between environment CHO mouth rinsing were detected (F = 0.37, df = 3, p = 0.80, g2p ¼ 0:01) (Fig. 4A). There was a significant effect between HH-CHO when compared to TN-CHO at 10 to 40 min and between HH-PLA when compared to TN-PLA at 20th to 40th min during exercise (p < 0.05, respectively). Similarly, mean Tsk revealed that a significant main effect on environment (F = 108.0, df = 3, p < 0.001, g2p ¼ 0:71), however no significant effect of CHO mouth rinsing (F = 0.42, df = 3, p = 0.71, g2p ¼ 0:01 and no interaction effect between environment CHO mouth rinsing were detected (F = 0.58, df = 3, p = 0.60, g2p ¼ 0:01) (Fig. 4B). There was a significant effect between HH-CHO when compared to TN-CHO and between HH-PLA when compared to TN-PLA throughout the exercise (p < 0.05, respectively). Psychological Response Mean RPE value increased during the exercise averaging at 18 ± 1, 18 ± 1, 18 ± 1 and 18 ± 1 for TN-CHO, HH-CHO, TN-PLA and HH-PLA at exhaustion, respectively (Fig. 5A). There was a significant effect of time (F = 1334.3, df = 3, p < 0.001, ηp2 = 0.97). Statistical analysis revealed that a significant main effect on environment (F = 12.0, df = 3, p < 0.001, ηp2 = 0.21), however no significant effect of CHO mouth rinsing (F = 0.04, df = 3, p = 0.99, ηp2 = 0.01 and no interaction effect between environment CHO mouth rinsing were detected (F = 0.83, df = 3, p = 0.48, ηp2 = 0.02) (Fig. 5A). There was a significant effect between HH-CHO when compared to TN-CHO and between HH-PLA when compared to TN-PLA at 30th to 45th min
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during exercise (p < 0.05, respectively). The perceived activation scale (FAS) and feeling scale (FS) shown a significant difference in HH when compared to TN environments (p < 0.001), respectively (Fig. 5B and C). There no significant difference in gastrointestinal comfort between trials (p > 0.001) (Fig. 5D). 38.0
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Fig. 5. Rating perceived exertion (a), perceived activation scale (b), feeling scale (c) and Gastrointestinal comfort (d) for TN-CHO, HH-CHO, TN-PLA and HH-PLA. TN: thermoneutral; HH: hot-humid; CHO: carbohydrate; PLA: placebo AU: arbitrary unit. Data are presented as mean ± SD. *Significant difference between TN and HH (CHO vs PLA; p < 0.05); #Significant effect of time (p < 0.05).
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4 Discussion The aim of this study was to examine the influence the environmental condition on time to exhaustion (TTE) of running performance across a thermoneutral (TN) and a hothumid (HH) environmental condition while performing mouth rinsing with a carbohydrate (CHO) and a placebo (PLA) solution. To the best of our knowledge, this is a novel systematic study to investigate if the environmental condition has a direct influence on the outcome of CHO mouth rinsing during the running exercise performance. The main finding of this study was that that the mouth rinsing intervention, regardless of the solution type, improved endurance running performance in TN but not in a HH condition. The magnitude of improvement for the TTE was greater while rinsing CHO as compared to the PLA solution across the two environmental conditions [31.8% improvement for CHO trials (TN vs HH) and 28.6% improvement for PLA trials (TN vs HH)]. Numerous studies have demonstrated an improvement in the TTE of running exercise in a temperate (20–21 °C and 50–60% RH) conditions with CHO mouth rising, while experiencing similar physiological (i.e., HR, VO2) and perceived psychological state (i.e., RPE) level of stress as compared to a PLA intervention (Fares and Kayser 2011). In this study, during submaximal exercise in HH environment (30 ° C and 70% RH) resulted in a comparable physiological and psychological responses between CHO and PLA mouth rising trials yet does not elicit in time performance difference (Fig. 2). A similar finding was observed while exercising in 32 °C and 75% RH, where CHO mouth rinsing lack of ergogenic benefits to cycling performance (10 km time trial), perhaps may be due to shorter time trial duration (*12 min) (Che Muhamed et al. 2014). The study by Watson and colleagues (2014) revealed that CHO mouth rinsing does not enhance 1 h cycling exercise performance in heat stress environment (30 °C and 60% RH) compared to PLA solution. Nevertheless, the reason for the lessened effectiveness of CHO mouth rinsing during the performance in the heat stress environment remains uncertain. Thus, the present data have shown that the difference in environment conditions (HH and TN) may be the key factor in the effectiveness of CHO mouth rinsing during exercise. The elevated in physiological strain due to thermal-mediated may be more influential in regulating perceived exertion when exercising in the heat stress environment. This is observed by the rapid rise of Tre and Tsk (Fig. 4) in HH compared to TN environment, along with the associated development of cardiovascular strain (i.e., HR; Fig. 3b) between environments, which influence the exercise performance (Fig. 2) and RPE (Fig. 5a). The notion of CHO mouth rinsing in TN environment seems to be effective through stimulation of CHO oral receptors that link to activated various brain regions that link with reward and motivation, resulting in superior exercise capability at given RPE (Chambers et al. 2009). The data shown the RPE (Fig. 5A), were slightly lower at the later stages of the exercise, suggesting that the subjects able to exert higher running capability at a lower rate of RPE. Similarly, perceived arousal level (Fig. 5B) were amplified with CHO mouth rinsing in TN when compared to HH conditions, suggesting the runners experiencing elevated of feeling for pleasure during the exercise (Rollo et al. 2008). However, when exercising in hot-humid conditions, it has been
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proposed that the afferent sensory output from heart, muscle, thermoreceptors and respiratory system (Ray and Gracey 1997; Schepers and Ringkamp 2010) may have counteracted with this response, subsequently affecting exercise performance. The elevated Tre and Tsk during exercise in heat stress environment may result in reduced in cardiac output due to increased internal heat transfer from muscle to facilitated heat transfer to the skin while preserving mean arterial pressure (Gonzalez-Alonso et al. 2008; Rowell 1986). The data in the present study clearly show that the Tre and Tsk (Figs. 6.7 and 6.8) steadily increased throughout the exercise for HH when compared to TH environment, a potentially higher thermal strain that primarily causes to weakening submaximal aerobic exercise capacity in the heat stress environment (Sawka et al. 2012). The rapid increased of Tre was observed as early 10 min during exercise in HH trials (Fig. 4a) and concomitantly higher HR (Fig. 3b) response may indicate an early thermal strain resulted in less time performance compared to TN trials. Subjects in the current study were pre-dehydrated (*2% body mass deficits) prior to TTE running and continue to lose an amount of body fluid at the end of the exercise trials (3.8%–4.5% body mass deficits) (Table 2). It is currently known that hydration status is not the major factor influencing the physical performance of athletes during exercise (Cheung et al. 2015; Goulet 2011; Noakes 2003; Wall et al. 2015). The performance enhancement with CHO mouth rinsing observed among dehydrated subjects (*4% body mass deficits) may be due to the less thermal strain that enables the maximum effect of mouth rinsing the influence the specific brain activation. Indeed, a recent study revealed that CHO mouth rinsing among dehydrated subject enhances running performance when compared to the euhydrated state (Kamaruddin et al. 2019). Yet the oral sensing via the thirst sensation when dehydrated increase the magnitude of brain signal when the subject felt the CHO is rewarding (de Araujo et al. 2003). However, an exercise in heat stress environment with dehydration, pose a detrimental effect on cardiovascular and thermoregulatory functions (Montain and Coyle 1992) thus can lead to a reduction of aerobic capacity and power output (Adam et al. 2008; Gonzalez-Alonso et al. 1997; Nybo 2010). This can be observed by higher HR, Tre, Tsk and Tb during the early part of the TTE in both CHO or PLA mouth rinsing during HH compared TN trials, possibly due to the of dehydration and thermal stress (Fig. 4a, b). Our findings demonstrated a distinct influence of the environmental condition on the efficacy of CHO mouth rinsing and endurance running exercise performance. The present study demonstrated that the increased in cardiovascular and physiological strain (i.e. a significant rise in HR, Tre, Tsk and Tb) during the exhaustive running exercise observed in a heat stress environment (HH) were the key reasons to decreased exercise performance when compared to a cooler environment (TN). This was the first study that had systematically examined the effectiveness of CHO mouth rinsing on endurance running exercise performance across two different environmental conditions. It would appear that greater thermal and cardiovascular strain resulted in additional afferents signal that could counteract any possible ergogenic effect of CHO mouth rinsing in the heat. It was concluded that the increased of thermal strain during TTE running performance in heat stress is associated with a performance-restrictive in cardiovascular strain, may the key reason to attenuated exercise performance.
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Ramanathan, N.L.: A new weighting system for mean surface temperature of the human body. J. Appl. Physiol. 19, 531–533 (1964) Ray, C.A., Gracey, K.H.: Augmentation of exercise-induced muscle sympathetic nerve activity during muscle heating. J. Appl. Physiol. (1985) 82(6), 1719–1725 (1997) Rollo, I., Cole, M., Miller, R., Williams, C.: Influence of mouth rinsing a carbohydrate solution on 1-h running performance. Med. Sci. Sports Exerc. 42(4), 798–804 (2010). https://doi.org/ 10.1249/MSS.0b013e3181bac6e4 Rollo, I., Homewood, G., Williams, C., Carter, J., Goosey-Tolfrey, V.L.: The influence of carbohydrate mouth rinse on self-selected intermittent running performance. Int J Sport Nutr Exerc. Metab. 25(6), 550–558 (2015). https://doi.org/10.1123/ijsnem.2015-0001 Rollo, I., Williams, C.: Influence of ingesting a carbohydrate-electrolyte solution before and during a 1-hour run in fed endurance-trained runners. J. Sports Sci. 28(6), 593–601 (2010). https://doi.org/10.1080/02640410903582784 Rollo, I., Williams, C., Gant, N., Nute, M.: The influence of carbohydrate mouth rinse on selfselected speeds during a 30-min treadmill run. Int J Sport Nutr Exerc. Metab. 18(6), 585–600 (2008) Rowell, L.B.: Human Circulation: Regulation During Physical Stress. Oxford University Press, USA (1986) Rowell, L.B., Marx, H.J., Bruce, R.A., Conn, R.D., Kusumi, F.: Reductions in cardiac output, central blood volume, and stroke volume with thermal stress in normal men during exercise. J. Clin. Invest. 45(11), 1801–1816 (1966). https://doi.org/10.1172/jci105484 Sawka, M.N., Cheuvront, S.N., Kenefick, R.W.: High skin temperature and hypohydration impair aerobic performance. Exp. Physiol. 97(3), 327–332 (2012). https://doi.org/10.1113/ expphysiol.2011.061002 Schepers, R.J., Ringkamp, M.: Thermoreceptors and thermosensitive afferents. Neurosci. Biobehav. Rev. 34(2), 177–184 (2010). https://doi.org/10.1016/j.neubiorev.2009.10.003 Svebak, S., Murgatroyd, S.: Metamotivational dominance: a multimethod validation of reversal theory constructs. J. Pers. Soc. Psychol. 48(1), 107 (1985) Tatterson, A.J., Hahn, A.G., Martin, D.T., Febbraio, M.A.: Effects of heat stress on physiological responses and exercise performance in elite cyclists. J. Sci. Med. Sport 3(2), 186–193 (2000) Tucker, R.: The anticipatory regulation of performance: the physiological basis for pacing strategies and the development of a perception-based model for exercise performance. Br. J. Sports Med. 43(6), 392–400 (2009). https://doi.org/10.1136/bjsm.2008.050799 Wall, B.A., Watson, G., Peiffer, J.J., Abbiss, C.R., Siegel, R., Laursen, P.B.: Current hydration guidelines are erroneous: dehydration does not impair exercise performance in the heat. Br. J. Sports Med. 49(16), 1077–1083 (2015). https://doi.org/10.1136/bjsports-2013-092417 Watson, P., Nichols, D., Cordery, P.: Mouth rinsing with a carbohydrate solution does not influence cycle time trial performance in the heat. Appl. Physiol. Nutr. Metab. 39(9), 1064– 1069 (2014). https://doi.org/10.1139/apnm-2013-0413 Wingo, J.E., Lafrenz, A.J., Ganio, M.S., Edwards, G.L., Cureton, K.J.: Cardiovascular drift is related to reduced maximal oxygen uptake during heat stress. Med. Sci. Sports Exerc. 37(2), 248–255 (2005) Yamashita, N., Ito, R., Nakano, M., Matsumoto, T.: Two percent hypohydration does not impair self-selected high-intensity intermittent exercise performance. J. Strength Cond. Res. 29(1), 116–125 (2015). https://doi.org/10.1519/jsc.0000000000000594
Which Joint Angle Changes Have Most Influence on Dart Release Speed? Nurhidayah Omar(&), Farah Syahida Abdul Nasir, and Ahmad Faizal Salleh Universiti Malaysia Perlis, 02600 Arau, Malaysia [email protected]
Abstract. A three-segment angle-driven model of dart throwing was developed to observe which joint angle of the upper limbs has most influence on the dart release speed. A subject performing 10 dart throwing trials were recorded using a motion analysis system. Subsequently, the joint angle time histories of individual trial were put in into the simulation model. The model calculated resultant dart release speed for each recorded trial and each trial was matched accurately. Systematically substituting a constant value to each joint angle, and observing the changes on dart release speed indicated that dart release speed was most susceptible to forearm extension/flexion. During coaching or performance, attention should be focused on this joint angle because any changes could have a substantial effect on the dart release speed. Keywords: Simulation
Angle-driven model Sports biomechanics
1 Introduction The objective of dart throwing is to let the dart rest on a certain location on the scoring bed especially on the bull’s eye. The location at which a thrown dart will hit the board depends on a combination of the dart’s initial conditions, specifically, position, velocity, and direction of motion at the moment of release if the rotation and air resistance are negligible [1, 3–5, 8]. Additionally, the dart’s oscillation frequency was highly correlated to launch speed [7]. The speed of the throw is vital because if the throw is too slow, the dart will take more time to reach the scoring board which will result the dart to land too low. Conversely, if the throwing speed is too fast, the dart will end too high on the scoring bed. The dart throwing manoeuvre is performed in a stable situation by a single upper limb without involving whole body movements or translation. The movement is relatively simple because it excludes the complexity created by motion of multiple joints [6] and is predominantly conducted using elbow flexion and extension [8]. However just like any other throwing sports, change in kinematic of the arm will change the performance of dart throwing. Since the speed of dart at release is one of the important criteria in dart throwing manoeuvre, the purpose of this study is to observe which segment/joint angle will influence more on dart speed at release.
© Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 164–169, 2020. https://doi.org/10.1007/978-981-15-3270-2_17
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2 Methodology 2.1
Experiment
Kinematic data of a female dart thrower (age: 21 years, mass: 48 kg, height: 159 m) was collected using five Oqus (Qualisys Track Manager) camera motion analysis system operated at 125 Hz. Fifty markers were affixed to the subject’s body, with 3 markers to create head segment, 17 markers on the upper body and 30 markers on the lower body. Next, Visual3D software was used to create bone as a visual of subject body. Joint angle, angular velocity and joint torque from experiment were subsequently calculated using this software. A dart board was hung at 1.55 m above the floor so that the centre of the bull’s eye is at the subject eye-level. A dart weigh 18 g was used in this study. Distance between the thrower front foot and the position of dart board was set to the regulation throwing distance which is 2.37 m. The subject required to perform 10 successful maximum effort dart throw from flat-ground towards the dartboard. Anthropometric measurements of the subject were taken and used as an input into the angle-driven model. 2.2
Simulation Model
Kane’s method was utilised to derive the equations of motion for the three segment angle-driven model which was formulated using the AutolevTM software package (version 3.4). Massless linear springs (Eq. 1) was used to model the interaction between the hand segment and the dart in x-axis and y-axis. The springs force is dependent on the position and velocity of the springs. F ¼ kx b_x;
ð1Þ
where F is the spring force in the spring, k is the stiffness coefficient, x is the depression, b is the damping coefficient and x_ is the velocity. The linear springs was included in the model so that it will grip the dart in place and minimise the movement. The value of the coefficients for stiffness (k) and damping (b) parameters were settled at 1000 Nm−1 and 1000 Nsm−1 respectively. These values are decided based on the values used in preceding studies on fast bowling cricket [9] and technique in overarm throwing [10] successfully. Dart release in the experimental data occurred when the dart could no-longer be within the hand based upon geometry. It was considered that there are no forces acting on the dart in the horizontal direction. On the other hand, gravity was presumably to act on the dart in the vertical direction. Equations of constant acceleration were then used to calculate the dart release velocities. The model had three-segments, i.e., upper arm, forearm and hand. The segments were connected together using frictionless pin joint (Fig. 1). Dart is modeled as a point-mass attached at distal end of distal segment.
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Fig. 1. Three segments developed in the angle-driven model.
An angle-driven model is a model which is functioned using the kinematics data from a real performance (Figs. 2, 3 and 4) meaning that the joint angles are predetermined (from experiment) when make use of an angle-driven model. Thus, the technique is similar to that actually used.
Upper arm rotation 120 Velocity (m/s)
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Fig. 2. Upper arm rotation at shoulder. Straight line: model; dotted line: experiment. Dart release at zero.
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Fig. 4. Hand rotation at wrist. Straight line: model; dotted line: experiment. Dart release at zero.
Angle-driven models along with the joint angles obtained from the 10 successful trials were employed to examine which joint angle has more influence on the dart speed at release. At the beginning, the time history of individual joint angle was examined. This process was repeated for all 10 successful trials. Subsequently, the angle-driven model was utilised to examine how by permitting single joint angle to be constant can influence the dart release speed. The constant is the value of the specific joint angle at ball release.
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3 Results 3.1
Model Evaluation
Compatible result was found with the average difference in resultant dart speed between the angle-driven model and the experiment of 0.16 m/s (5.07 m/s from experiment, 5.23 m/s from model) when all joint angles were allowed to vary as they did in each actual performance. This demonstrated that the model used was adequate to investigate dart throwing. 3.2
Simulation
Table 1 presented the mean differences in dart release speed as individual joint angle was kept constant. A positive value indicates the dart release speed is increasing, while a negative value denotes the dart release speed is decreasing. Table 1. Mean differences in dart release speed when respective joint angle was kept constant. Joint angle Shoulder extension/flexion Elbow extension/flexion Wrist flexion/extension
Changes in x-axis (m/s) 0:52 m/s
Changes in y-axis (m/s) þ 0:44 m/s
Changes in resultant speed 0:29 m/s
3:73 m/s
0:27 m/s
4:06 m/s
0:63 m/s
1:75 m/s
0:99 m/s
4 Discussion and Conclusion The aim of this study was to observe how a segment/joint angle can affect dart speed at release. The results showed that the dart release speed is highly influenced by forearm orientation. This finding is in accordance with the one found by [8] which stated that the dart throwing is mainly controlled by elbow flexion and extension. The role of the shoulder and wrist are to yield a stable platform for the momentum generation and accuracy of the hand during the throw [11]. Although the throw speed in this study is 5.07 m/s (experiment) which is a little slower, it is comparable with previous studies where the throwing speed lies in the range 5.0–7.5 m/s [1, 2, 7]. This is presumably because the subject in this study is a novice female dart thrower. In future experimental data of competitive dart throwers will be considered. In this study, hand segment has been modelled as one segment. To represent a more real dart throwing manoeuvre, hand segment could be modelled as two segments – metacarpal and finger segments so that contribution of finger segment on dart speed can be observed.
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As a conclusion, the model provides theoretical predictions on which segment/joint angle influenced the most on dart speed at release. The model highlighted that the dart release speed was sensitive to forearm orientation.
References 1. Smeets, J.B., Frens, M.A., Brenner, E.: Throwing darts: timing is not the limiting factor. Exp. Brain Res. 144, 268–274 (2002) 2. Venkadesan, M., Mahadevan, L.: Optimal strategies for throwing accurately. Roy. Soc. Open Sci. 4, 170136 (2017) 3. Dupuy, M.A., Mottet, D., Ripoll, H.: The regulation of release parameters in underarm precision throwing. J. Sports Sci. 18, 375–382 (2000) 4. Nasu, D., Matsuo, T.: Variability in timing and range of the time window of release in darts throwing: a comparison between experts and novices. In: 31st International Conference on Biomechanics in Sports Proceedings, Japan (2013) 5. Campos, C.E., Lage, G.M., Andrade, A.G.P., Cuoto, C.R., Santos, S.P., Profeta, V.L.S., Ugrinowitsch, H.: Changes on movement control of dart throwing under distance and target weight constraints. J. Hum. Sport Exerc. 4(14), 1–10 (2019) 6. Shiraki, Y., Yamamoto, S., Kushiro, K.: Effects of different modes of preparatory motion on dart throwing performance. Compr. Psychol. 4(12), 1–5 (2015) 7. James, D., Potts, J.: Experimental validation of dynamic stability analysis applied to dart flight. Sports Eng. 21, 347–358 (2018) 8. Nasu, D., Matsuo, T., Kadota, K.: Two types of motor strategy for accurate dart throwing. PLoS One 9(2), 1–9 (2014) 9. Felton, P.J.: Factors limiting fast bowling performance in cricket. Ph.D. Dissertation, Loughborough University, UK (2014) 10. Omar, N.: Technique in overarm throwing. Ph.D. Dissertation, Loughborough University, UK (2016) 11. Wolfe, S.W., Crisco, J.J., Orr, C.M., Marzke, M.W.: The dart throwing motion of the wrist: is it unique to humans? J. Hand Surg. 31(9), 1429–1437 (2006)
The Influence of Anthropometrics, Physical Fitness, and Technical Skill on Performance of U-12 Youth Soccer Players in Malaysia Ahmad Bisyri Husin Musawi Maliki1, Mohamad Razali Abdullah1(&), Mohamad Shafaat Fadzil2, Muhd Faris Nazer2, Muhammad Hafiz Zufaimey Ismail2, Khairie Koh Abd Hadi Koh2, Noraini Nazarudin2, Siti Musliha Mat-Rasid1, Mohd Syaiful Nizam Abu Hassan2, Amr Alnaimat1, Muhammad Rabani Hashim1, Hafizan Juahir1, and Rabiu Muazu Musa3 1
East Coast Environmental Research Institute (ESERI), Universiti Sultan Zainal Abidin, 21300 Kuala Terengganu, Terengganu, Malaysia [email protected] 2 Faculty of Applied Social Sciences, Universiti Sultan Zainal Abidin, 21300 Kuala Terengganu, Terengganu, Malaysia 3 Centre for Fundamental and Liberal Education, Universiti Malaysia Terengganu, Kuala Nerus, 21030 Kuala Terengganu, Terengganu, Malaysia
Abstract. The present study is aimed at developing a capability index for performance in soccer and explore its differences with regards to specific skills and fitness-related attributes in the sport. A total of 87 adolescent soccer athletes aged 12 years old were recruited as participants. Relative performance namely anthropometrics, physical fitness, and soccer technical skill are assessed as dependent variables. The Principal Component Analysis (PCA), Cluster Analysis (CA) and Discriminant Analysis (DA) were used to achieve the purpose of this study. The CA analysis grouped the performance of the players into three different clusters namely; high (18 players), moderate (45 players) and low (24 players). The PCA reveals a moderate to very strong dominant range of 0.63 to 0.96 of factor loading on soccer performance. The DA analysis was applied with the defined clusters as independent variables (IV) whilst the physical, fitness, as well as the skill attributes are treated as dependent variables. It was demonstrated that a number of performance related variables could differentiate the relative performances of the players. The findings from the study highlighted the dominant attributes of U-12 Malaysian youth soccer players which could be beneficial to the coaches and players in identifying the suitable biological and physiological variables inherent to the soccer relative performance. Keywords: Soccer Anthropometric Soccer relative performance Physical Fitness
© Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 170–179, 2020. https://doi.org/10.1007/978-981-15-3270-2_18
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1 Introduction Modeling the talent and skills of a football player is a priority in the selection of athletes. Anthropometrics, physiology, and skills are closely linked to the success of a soccer team. The size and position of the body and the body parts that each athlete possesses are one of the influential factors in the performance of the athlete, especially in soccer. Therefore, various anthropometric factors, physical fitness, skills and psychology of soccer have been investigated in predicting the potential of soccer players [1]. The ideal could contribute towards a higher level of performance in the sport of soccer. However, excess weight is directly linked to a reduction of player’s agility [2]. In the soccer domain, physical, anthropometric, technical and physiological fitness are reported as important elements for improving soccer performance [3]. This view is shared by professionals in youth soccer, who also suggest elite players characterized by obesity, fat mass, muscle mass, strength, and speed [4]. In a soccer team, utilizing players based on their specific roles is required. Thus, it is important to measure precise performance by identifying the most important attributes for each player [5]. Anthropometric potential, as well as body composition, receive little attention from coaches. More attentions were largely devoted to technical skills rather than physical fitness and anthropometric features. Nonetheless, it is worth mentioning that the body composition of a player plays an important role in determining the players’ performance on the field [6]. This will allow the coach to identify the exact attributes and physical characteristics of each player. Therefore, this study aims to explore the most influential factors affecting football performance and to identify the differences in Anthropometrics, Physical Fitness, and Technical Skill in Malaysia Youth Soccer Performance.
2 Material and Method All current study methods such as anthropometric tests, battery tests, football and special battery tests related to soccer have been performed in accordance with the following procedures. 2.1
Participants
This current study uses a random sampling technique consists of youth soccer players from the Malaysian football academies by merging the designs of the study. A total of 87 youth soccer players with an average age of 12 years volunteered to take part in this study. All of the protocols and procedures are officially approved by the University Human Research Committee of Ethics before the data are collected (UniSZA/02/1/2016/Jil.207). Moreover, the participants have been informed about the objectives of the study and consent agreement was obtained. 2.2
Anthropometrics
Anthropometrics tests are done to measure weight, standing upright, sitting height, and four different body fat areas. Weight is assessed by using the standard electronic
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advanced scale at the nearest 0.1 kg, in the interim standing position to measure the nearest 0.5 cm. Meanwhile, chronological age is measured starting from the birth of the participants until the day of the test. For sitting height, the measurement is taken from the highest point of the head to the base and is recorded to the nearest 0.5 cm. All procedures are recorded twice and the mean score is recorded to assist the further analysis. 2.3
Soccer Battery Test
Assessment of muscle strength is measured as the recommended way to assess physical fitness. This physical fitness test performance is recorded based on six parameters which are a 10 m speed, 30 side jumps, 1-min push up, standing jump (cm), VO2max. Shuttle run is usually used to measure an individual’s agility [7]. Agility is one of the indispensable physical health components in all activities that require the speed of change in body position and its parts [8]. Mark two lines 10 m apart using a marking tape or cones. Both cones are placed at the starting line and the end line, each. At the “ready” signal, participants place their front legs behind the starting line. About the signal, “go!” participants sprint in the opposite direction, touch the cone and sprint back to the starting line. The routine is repeated five times. Stopwatch and timing or speed gates are used to calculate and record the time taken by each participant during the sit-up test and agility tests. The sit-up test is conducted to measure the strength and the toughness of abdominals and hip muscles. For calculation, the sit-up maximum routine of set undertaken for recorded. Push-up exercises are very popular in upperbody strengthening programs. The standard push-up can be used either in the assessment of muscle performance or as an exercise to increase chest, shoulder and arm strength [9]. Standard push-ups begin with the hands and toes touching the floor, body, and feet in a straight line, feet slightly apart, arms at shoulder-width apart, extended and at right angles to the body. Keeping the back and knees straight, the subject lowers to a predetermined point, to touch several other objects, or to a 90-degree angle to the elbow, then back to the starting position with the extended arm. This action is repeated, and the test continues until fatigue, or until they are unable to do anything else in the rhythm or have reached the target number of push-ups. The Standing Jump also called the Broad Jump, is common and easy to administer test of explosive leg power. Standing jumps are generally considered to be a power test, demonstrating the ability to release maximum muscle power in a short time [10] which is two-foot take-off and landing is used, with swinging of the arms and bending of the knees to provide forward drive. Broad jumps are just as important as vertical jumps to measure explosive power. Although they use essentially the same muscles, each routine represents separate skills [11]. This viewpoint is substantiated by several researchers. 2.4
Soccer Technical/Specific Skills
A special soccer skill test has been conducted to obtain the technical characteristics of the skills by applying from the previous study, F-MARC test. It works to measure skill tests such as dribbling with and without balls, ball controlling using three different body parts. There are two types of dribbling; without the ball, which focuses on speed,
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and with ball, which focuses on touch and control [12]. The ball control test is usually used mainly to measure trapping ability [13]. Time and speed are recorded and evaluated during the test [5]. Moreover, for the juggling test, the number of times players touch the ball before it bounces on the ground is recorded. 2.5
Data Analysis
Principal component analysis (PCA) is conducted to examine the data. PCA anticipation such as the adequacy of samplings and the sphericity tests is calculated before the analysis. By means of the PCA, anthropometric index, and maturity will be developed into different categories of groups. Although some parameters are not normally distributed, the main analysis is calculated as suggested by the previous research stating that it is normal to have abnormal data to be distributed in human performance due to variation of personalities [14]. The Univariate clustering is also used to determine the index performance of the players. The core algorithm minimizes the amount of distance in the cluster using their respective metrics. It will be divided into different groups consisting of Low Potential Group (LPG), Moderate Potential Group (MPG) and Potential Group (PG). Besides, researchers also use Discriminant Analysis (DA) to examine the differences groups in the soccer performances. Equations 1 and 2 are used to analyze the PCA as well as the DA in this study respectively. Zij ¼ af 1 f2i þ afm fmi þ efi f ðG I Þ ¼ k i þ
n X
Wij Pij
ð1Þ ð2Þ
i¼1
3 Result and Discussion It can be seen from Fig. 1 that PCA identifies four components as the most important factors because of higher eigenvalues (>1). Further analysis is carried out via varimax rotation by using two new latent factors. The PCA pattern after the varimax rotation is revealed in Fig. 1. It can be seen that the effect of variance for PCA1 (43.9%) and PCA2 (39.2%) with cumulative variance is 83.1%. There are four main components. The first factor (PCA1) satisfied with the factor loading threshold. Table 1 shows that the first factor D1 (23.689%) which is about physical fitness that filled the threshold factor is 0.60 (weight, height, BMI). The findings suggest that body fat is important to monitor as it relates to the performance of football players. According to previous studies, the performance of soccer players (sprint) is closely related to the percentage change in body fat [15]. Aside from that, the percentage of fat body weight of potential group professional soccer players decreases significantly during the pre-season period and increases during the off-season. Therefore, this finding suggests the importance of body fat to be monitored as it has association with the soccer players’ performance [16].
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Scree plot 3.5 3
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Fig. 1. Scree plot of descriptive eigenvalue
Likewise, the second dominant factor D2 (15.559%) is aerobic capacity which identifies two components with higher positive factor loading such as (5 m, VO2max). These significant components are speed and agility training. The speed of play in today’s game is said to be faster than ever. Besides, faster players have a marked competitive edge. The physical capacity of athletes is an important element of success in sports achievements. Aerobic capacity is a major part of the metabolic processes that occur in the human organism and represents the bulk of the energy potential. Maximum oxygen intake (VO2max) refers to the aerobic intensity of the process and represents the capacity of the organism to use the maximum amount of oxygen at a given time. Even though these two processes are highly interrelated, maximum oxygen consumption has been considered by the previous researchers as the best indicator of the aerobic capacity of an individual, namely the ability of cardiovascular and respiratory system functions, and tissue capacity to utilize oxygen [17]. At the same time, it is the best indicator of physical athlete ability. The rest is the D3 component (10.863%) as the third most important factor in ball control or skill. Speed, skill, and strength are the most important driving qualities in football [18]. The physical capacity of a football player can be tested by various physical fitness tests. Soccer fitness tests can be divided into laboratory tests and football-specific field tests. Although laboratory tests are considered reliable and useful in measuring general fitness levels, their validity in measuring specific football capacity has been questioned [19]. Specific training and tactics and appropriate training management can improve their performance. Rather than focusing solely on maximal performance, it can prove beneficial to place greater emphasis on understanding
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efficiency (movement control) during these movements. The same can be applied, for example, in terms of running mechanics/technique [20]. Meanwhile, sit-ups, push-ups are major factors in D4 (13.813%), meeting the loadbearing factor of the factor which is a test of soccer fitness. Fitness tests are also more specialized in the measurement of fitness for athletes to measure training intensity and identify strengths and weaknesses [19]. Soccer players performing at a low level (low potential) are less able to sustain high-intensity work during a competitive match [21]. Therefore, potential group footballers must be able to stabilize their current level of performance and maintain their intensity rate consistently for a maximum period.
Table 1. Factor loadings after Varimax rotation Variables Height (Cm) Weight (Kg) Bmi 10*5 M (Sec) 30 s Side jump (rep) 1 Min sit up (rep) 1 Min push (rep) Standing jump (Cm) VO2max W/out ball (Sec) With ball (Sec) Juggling (rep) Eigenvalue Variability (%) Cumulative %
D1 0.72 0.97 0.89 −0.24 −0.08 0.06 −0.29 0.58 −0.20 −0.13 0.20 −0.09 3.30 23.69 23.69
D2 0.48 0.09 −0.25 −0.73 0.51 0.20 0.06 0.58 0.63 0.04 −0.05 −0.07 1.98 15.56 39.25
D3 −0.05 −0.04 −0.04 0.00 0.47 −0.20 0.06 0.04 −0.04 0.56 0.72 0.44 1.31 10.86 50.11
D4 −0.30 −0.17 0.01 −0.08 0.01 0.79 0.75 −0.09 0.19 0.08 −0.19 0.50 1.08 13.81 63.93
Subsequently, further analysis is calculated using the anthropometric, physical fitness and technical skill by using PCA output. The anthropometric, physical fitness and technical skill are based on the most dominant component following producing three sets of different performance categories which is LPG, MPG and the PG as shown in Table 2. This table also shows the cumulative frequency of players in each group. Based on Table 2, the indices explain that a total of 24 players comprising low potential, 45 moderate potential, and 18 potential players, respectively. Based on the soccer performance results, each group is analyzed by finding the variations of the soccer performance Index by means of DA to determine the difference between the three predetermined groups. Mean descriptive statistics for body size, aerobic capacity,
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football-specific skills and soccer fitness for players in three soccer performance groups are summarized in Table 2. High soccer performance players lack juggling, run without ball, and also routines not involving calves and hamstrings (side jump). The previous study shows that the different positions on the field are characterized by specific physical activities and demands [22]. It should be noted that physical profiles, along with technical and tactical skills are important determinants of player level [23]. Other studies have shown that player level affects activity patterns in the field [15]. High-level players not only cover higher distances but also perform highintensity activities [24] during football games compared to lower-level players. Therefore, individualization of training, based on the field’s position and individual weaknesses, is important to enhance performance during football games. Table 2. Index status of anthropometric, physical fitness, technical skill. Score −71.3 −17.4 25.8
Freq. 24 45 18
Cum. freq. % Group range 24 27.6 −71.3 LPG < −17.4 69 51.7 −17.4 MPG < 25.8 87 20.7 PG 25.8
Performance Low potential Moderate potential Potential group
Table 2 shows the athlete’s classification concerning their performance group determined by Univariate clustering, which is based on the degree of relative performance similarity. It shows a group profile plot for each group of relative performances. The figure illustrates an athlete’s performance based on the examined variables. This merger allows the classification and assignment of performance-related components to athletes and thereby leads us to further analysis for athlete authentication and differentiation. Table 3 displays the discrimination analysis conducted between the groups with regards to the examined performance variables. The table shows the performance differences of the soccer players based on the twelve performance parameters discriminated by DA. Some methods are selected to perform the DA which is standard, backward stepwise and forward stepwise. The preciseness of classification using standard stepwise is 93.1% (twelve independent variables), forward stepwise 91.9% (three independence variables which are weight, 10*5 and standing jump) and backward stepwise 93.1% (five independence variables such as height, weight, BMI, 10 m*5 and standing jump), respectively.
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Table 3. Classification matrix of Discriminant Analysis (DA) or the relative performance variations on the three different groups of the players From\To % Correct Groups assigned by DA LPG PG MPG Standard mode (12 Variables) LPG 87.50% 21 0 3 PG 88.89% 0 16 2 MPG 97.78% 1 0 44 Total 93.10% 22 16 49 Forward stepwise (3 Variables) LPG 87.50% 21 0 3 PG 83.33% 0 15 3 MPG 97.78% 1 0 44 Total 91.95% 22 15 50 Backward stepwise (5 Variables) LPG 91.67% 22 0 2 PG 83.33% 0 15 3 MPG 97.78% 1 0 44 Total 93.10% 23 15 49
4 Conclusion The findings of the present study identified the variables of anthropometrics, physical fitness as well as technical skill influencing the performance of U-12 Malaysian soccer players. Although, it is worth to mention that the variables investigated in the present study did not include the cognitive, tactical and biomechanical elements of performance which are generally laboratory-based. However, the findings from the study demonstrate that the variables selected could significantly differentiate the performance levels of the players examined. Thus, the various fitness indicators evaluated might be useful to the coaches and players in identifying the strengths and weaknesses of the players from the aforesaid performance variables. Nevertheless, it is worth to note that the findings of this study could only serve as a tool that may assist in designing training programs to suit the requirement of an individual player. Therefore, the selection or rejection of players must be based on a holistic approach by considering the characteristics related to physiology, anthropometry, psychology, as well as motor skill [25]. Acknowledgment. The author will like to thank the Research Management, Eseri, UniSZA, Malaysia Sports School and Nation Soccer Academy for their support, advice, and guidance for this study.
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References 1. Wilson, R.S., James, R.S., David, G., Hermann, E., Morgan, O.J., Niehaus, A.C., Hunter, A., Thake, D., Smith, M.D.: Multivariate analyses of individual variation in soccer skill as a tool for talent identification and development: utilising evolutionary theory in sports science. J. Sports Sci. 34(21), 2074–2086 (2016) 2. Thakur, J.: Association of obesity with agility and speed of university level kabaddi players. Intern J. Phys. Educ. Sports Health 3(2), 254–256 (2016) 3. Maliki, A.B.H.M., Abdullah, M.R., Juahir, H., Abdullah, F., Abdullah, N.A.S., Musa, R.M., Mat-Rasid, S.M., Adnan, A., Kosni, N.A., Muhamad, W.S.A.W., Nasir, N.A.M.: A multilateral modelling of Youth Soccer Performance Index (YSPI). In: IOP Conference Series: Materials Science and Engineering, vol. 342, no. 1, p. 012057. IOP Publishing (2018) 4. Martindale, R.J., Collins, D., Daubney, J.: Talent development: a guide for practice and research within sport. Quest 57(4), 353–375 (2005) 5. Abdullah, M.R., Maliki, A.B.H.M., Musa, R.M., Kosni, N.A., Juahir, H.: Intelligent prediction of soccer technical skill on youth soccer player’s relative performance using multivariate analysis and artificial neural network techniques. Int. J. Adv. Sci. Eng. Inf. Technol. 6(5), 668–674 (2016) 6. Abdullah, M.R., Musa, R.M., Maliki, A.B.H.M., Kosni, N.A., Suppiah, P.K.: Development of tablet application based notational analysis system and the establishment of its reliability in soccer. J. Phys. Educ. Sport 16(3), 951 (2016) 7. Deane, R.S., Chow, J.W., Tillman, M.D., Fournier, K.A.: Effects of hip flexor training on sprint, shuttle run, and vertical jump performance. J. Strength Cond. Res. 19(3), 615–621 (2005) 8. Little, T., Williams, A.: Specificity of Acceleration, Maximum Speed and Agility in Professional Soccer Players, pp. pp–144. Routledge, London (2003) 9. Cogley, R.M., Archambault, T.A., Fibeger, J.F., Koverman, M.M.: Comparison of muscle activation using various hand positions during the push-up exercise. J. Strength Cond. Res. 19(3), 628 (2005) 10. Bookwalter, K.W., Harrison, C.H.: Application of measurement to health and physical education (Book Review). Phys. Educ. 8(2), 57 (1951) 11. Clarke, H.H., Degutis, E.W.: Relationships between standing broad jump and various maturational, anthropometric, and strength tests of 12-year-old boys. Res. Q. Am. Assoc. Health Phys. Educ. Recreat. 35(3), 258–264 (1964) 12. Abdullah, M.R., Musa, R.M., Kosni, N.A., Maliki, A.B.H.M., Haque, M.: profiling and distinction of specific skills related performance and fitness level between senior and junior Malaysian youth soccer players. Int. J. Pharm. Res. 8(3), 64–71 (2016) 13. Fumoto, N., Kumagai, K.: Does a player whose ball juggling skill is the best shows the best ability in a soccer game?: a consideration of the validity of skill tests from a new viewpoint keeping utility in mind. Football Sci. 11, 18–28 (2014) 14. Salgado, J.F.: The five factor model of personality and job performance in the European Community. J. Appl. Psychol. 82(1), 30 (1997) 15. Ostojic, S.M.: Seasonal alterations in body composition and sprint performance of elite soccer players. J. Exerc. Physiol. 6(3), 11–14 (2003) 16. Maliki, A.B.H.M., Abdullah, M.R., Juahir, H., Muhamad, W.S.A.W., Nasir, N.A.M., Musa, R.M., Mat-Rasid, S.M., Adnan, A., Kosni, N.A., Abdullah, F., Abdullah, N.A.S.: The role of anthropometric, growth and maturity index (AGaMI) influencing youth soccer relative performance. In: IOP Conference Series: Materials Science and Engineering, vol. 342, no. 1, p. 012056. IOP Publishing (2018)
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17. Ranković, G., Mutavdžić, V., Toskić, D., Preljević, A., Kocić, M., Nedin-Ranković, G., Damjanović, N.: Aerobic capacity as an indicator in different kinds of sports. Bosnian J. Basic Med. Sci. 10(1), 44 (2010) 18. Monea, D., Prodan, R., Grosu, V.T.: Specific training for improving the skill and speed in junior football players. Timisoara Phys. Educ. Rehabil. J. 10(19), 207–215 (2017) 19. Aandstad, A., Simon, E.V.: Reliability and validity of the soccer specific INTER field test. J. Sports Sci. 31(13), 1383–1392 (2013) 20. Hewit, J.K., Cronin, J.B., Hume, P.A.: Kinematic factors affecting fast and slow straight and change-of-direction acceleration times. J. Strength Cond. Res. 27(1), 69–75 (2013) 21. Edwards, A.M., Macfadyen, A.M., Clark, N.: Test performance indicators from a single soccer specific fitness test differentiate between highly trained and recreationally active soccer players. J. Sports Med. Phys. Fitness 43(1), 14–20 (2003) 22. Boone, J., Vaeyens, R., Steyaert, A., Bossche, L.V., Bourgois, J.: Physical fitness of elite Belgian soccer players by player position. J. Strength Cond. Res. 26(8), 2051–2057 (2012) 23. Yusoff, N.I., Abdullah, M.R., Juahir, H., Lee, F., Low, J., Mat-Rasid, S.M., Zawi, M.K.: The effect of residence area on motor skill development among children. Indian J. Public Health Res. Dev. 10(3), 614–618 (2019) 24. Krustrup, P., Mohr, M., Ellingsgaard, H.E.L.G.A., Bangsbo, J.: Physical demands during an elite female soccer game: importance of training status. Med. Sci. Sports Exerc. 37(7), 1242 (2005) 25. Charles, M.A.G., Abdullah, M.R., Musa, R.M., Kosni, N.A.: The effectiveness of traditional games intervention program in the improvement of form one school-age children’s motor skills related performance components. J. Phys. Educ. Sport 17, 925–930 (2017)
Management and Sports Studies
Identifying Element of Academic Enhancement Support for Student-Athlete Using Fuzzy Delphi Method Mohd Zulfadli Rozali1(&) , Saifullizam Puteh1 , Faizal Amin Nur Yunus1 , Affero Ismail1 , and Thariq Khan Azizuddin Khan2 1
University Tun Hussein Onn Malaysia, 86400 Batu Pahat, Johor, Malaysia [email protected] 2 Sultan Idris Education University, Tanjong Malim, Malaysia
Abstract. Student-athletes who are enrolled at the undergraduate level in higher educational institutions in Malaysia have the challenge of raising their academic achievement. Preliminary survey shows that nearly 40% of studentathletes have cumulative grade point average (CGPA) below 3.00. This study aimed to develop a framework of academic enhancement support for studentathletes in Malaysian Public Universities. Problems, in order to improve academic achievement among student-athletes, are due to factors that do not support the improvement of academic achievement among student-athletes during their study sessions. As a result, student-athletes could not be maintained in the session of study, scholarship, and the implications from the result are they are not allowed to participate in training and also competition. Therefore, the purpose of this study was to identify elements of support to enhance academic achievement for student-athletes. Qualitative research approach involves 12 respondents representing academia, management institutions and the management of student-athletes to explore elements that could enhance academic achievement for student-athletes. A total of 12 experts representing academia, management institutions and the management of student-athletes were selected to analyze the fuzziness consensus of experts. All collected data were analyzed using the fuzzy Delphi method. The result of the analysis found that there are 22 elements that fulfill the requirement consensus of experts, which threshold value is equal and less than 0.2, the percentage of the expert group is more than 75%. Therefore, 22 elements of support to help undergraduate student-athletes at public universities to improve their academic achievement. Keywords: Academic enhancement support universities Fuzzy Delphi method
Student-athlete Public
1 Introduction Students are the main asset of each institution of higher education in which students academic achievements plays an important role in producing high-quality graduates to transfer on the social and economic growth of the country forward [1]. It is important © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 183–188, 2020. https://doi.org/10.1007/978-981-15-3270-2_19
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for the administration and lectures in higher education institutions to focus on the academic achievement of students in which even companies and industries are also interested to have for their company. Unlike others normal students in Higher Education Institution, student-athletes are the small part of the student population at each educational institution with roles within the campus, have patterns of life and the different needs in their study sessions [2]. As such, most student-athletes earn low academic grades and average score due to the amount of time mostly assigned to give commitments to physical exercise, where at the same time as a student where they have the responsibility to meet the requirements of academic (attending lectures, complete assignments, pass exams) during the study session [3].
2 Literature Review Most of the Higher Education Institution aims to produce students who earn good academic achievement but the environment of competition in sports and also their participation has resulted in the formation of a branch of cultural intellectual, poor academic performance among student-athletes and too dependent on other individuals from particular support in order to increase motivation for enhanced achievements in the academic and community environment [4, 5]. Some of them need to be monitored and support from their academic advisor to set their goals throughout their studies [15]. Most student-athletes setting in higher education institutions do not provide and nurture interest towards the development of academic achievement [6]. They just enrolled into study sessions at the university or college to cultivate their careers in sports. They achieved a CGPA of low dropout rate, the higher education level and the low percentage of study. According to some researcher that have the opinion about the studentathletes at the university achieve lower academic standards compared to students who do not involve in active sports [7–9]. The result of the findings by [5] found that the university administration and the role of coach didn’t help in developing studentathletes’ academic performance in Higher Learning Institution in Malaysia. Student-athletes are individuals who are experiencing stress in discharging its duties as an athlete and a student in an institution of learning [10]. This is because, the student-athletes are individuals who serve as full-time students at educational institutions and actively involved in sporting activities [11]. By such, the student-athletes involved actively at the university level or the international level should be given special attention and support as they need to cope with various forms of challenges and requirements during sessions of study [12]. Student-athletes in Higher Education Institution have to learn how to balance their responsibilities in terms of sports and also academic in ensuring balanced academic achievements such as the needs of the institution complied. As such, they should streamline the number of hours in the following sports training activities to ensure that they stay fit and at the same time committed to the academic regulations set by the institution. Sport in colleges and universities of the United States is hoped to be a part of student life, which sports could be given the same priority as academic needs for students to be able to involve in outdoor activities and to ensure that students can train their physical ability after undergoing routine and daily academic load [11].
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Without a clear understanding of the issues that can affect academic achievement of student-athletes, the sports administration and the Student Affairs was unable to formulate and provide services in support of student-athletes education sessions in education institutions in ensuring success in academia as a whole [1]. However, predicting academic achievement student-athletes is a challenge because this individual sessions study the same as ordinary students but have the burden of commitment and academic and sports at the same time.
3 Methodology Fuzzy Delphi Technique was used to explore the support element in environment aspect to help student-athletes at public universities to enhance their academic achievement which a set of questionnaire was developed by the researchers based on findings from the expert interviews. The interviews were conducted with 12 experts specialized in the field of student-athletes. In the second phase, a total of 12 experts were selected to answer the questionnaire. The number of respondents for Delphi technique is usually from 10 to 50, therefore, 12 experts were sufficient for this research [13]. Researchers have set the rationale for the selection of the sample for this face interview based on where (i) the expert is a person who is knowledgeable and expert in a matter of study and field of study as well as know about why and how to implement a thing in these areas (ii) work and have experience in the field for more than 5 year (iii) hold office in dealing with student-athletes for more than one term of study (iv) have the knowledge and are involved in managing the student-athletes in Malaysian public universities. The elements of environment aspects were identified by obtaining the consensus from the participating experts. Table 1 shows the simple Fuzzy Delphi procedures used in determining the domain. Table 1. Fuzzy Delphi Technique Phase No. of expert Instrument design Phase one 12 Semi- structured interview Phase two 12 Survey questionnaire
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Fuzzy Delphi procedures are composed of six basic steps as follows [14]: Step 1: Determination of Expert. A total of 11 experts were involved in answering the questionnaires. The experts were chosen based on their working experiences in the related field of expertise. Step 2: Linguistic Scale Selection. In this research, the linguistic scale comprised fivepoint scale, ranging from (1) strongly disagree, (2) disagree, (3) moderately agree, (4) agree, (5) strongly agree. The triangular fuzzy numbers (TFNs) are more proper to utilize as compare to the crisp numbers in the sense that it can represent the information more rigid in the real situation [14]. Table 2 shows the linguistic five-point scale:
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Strongly disagree Disagree Moderately agree Agree Strongly agree
0.0 0.0 0.2 0.4 0.6
Fuzzy scale 0.0 0.2 0.2 0.4 0.4 0.6 0.6 0.8 0.8 1.0
Step 3: Calculate the Average Value. The average value was calculated based on the total of linguistic scale number of each item and then divided by the number of experts. Step 4: Determine the Threshold Value (d). If the value of threshold (d) is equivalent to or smaller than 0.2, it indicates that the consensus and agreement from all experts are achieved. When threshold value is larger than 0.2, second round of data collection has to be conducted in order to fulfil the requirement for Fuzzy Delphi. Step 5: Consensus of Expert. In this stage, the percentages of consensus of each item and overall item have to be determined. If the consensus of experts is equal to or more than 75%, it indicates that the group has reached an agreement. The procedures have to be repeated to ensure the participating group has come to agreement provided the consensus percentage is less than 75%. Step 6: Defuzzification Process. The main function of defuzzification process is to determine the ranking and score of item by using one of the three formulas as follows: i. Amax = 1/3 * (m1 + m2 + m3) ii. Amax = 1/4 * (m1 + m2 + m3) iii. Amax = 1/6 * (m1 + m2 + m3) For the case of this research, the researchers have chosen formula (i) to obtain the defuzzified values as well as to determine the ranking and score according to the consensus of experts. 3.2
Data Analysis
The analysis outputs is based on the consensus from the participating experts indicated that three domain that important for student-athletes at public universities to enhance their academic achievement. From the three domain which is academic aspect, environment aspect and psychological- social aspect there will be twenty- two element from that three aspect that important in order to support student-athletes to enhance their academic achievement. The three domain that important for student-athletes at public universities to enhance their academic achievement are state in Table 3. Specifically, the results of analysis showed that the percentages of consensus for the three domain were larger than 75%, which is 88%. 98% and 98% and the threshold value, d for that three domain also below than 0.2.
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Table 3. Data analysis Aspect Academic Environment Psychological social
Threshold value, d 0.0123 0.0125 0.011
Consensus of expert (%) 88 98 98
4 Conclusion As a conclusion, Fuzzy Delphi Technique can be considered as an effective method to determine the constructs of a variable that based on the level of consensus among the experts. Fuzzy Delphi Technique consists of six basic steps, namely, selection of experts, linguistic scale selection, compute thee average value, calculate the threshold value, and determine the consensus of experts and lastly defuzzification process. The most important is the use Fuzzy Delphi Technique may significantly reduce time consumption on the questionnaire and save cost. In the other result aspect, the importance of element supports from environment aspects in providing support in order to enhance academic achievement on student-athlete’s public institutions of higher education cannot be denied. Academic achievement become the benchmark to rate of dropout students in Higher Education Institution. This study is important to the top management of university in addressing the problems of academic achievement student-athletes in an institution of higher learning. Through this research, it has a wide range of interest to several parties such as the top management of the University, faculty, and sport division of ministry of higher education. This study is important to the top management of university in addressing the problems of academic achievement student-athletes in an institution of higher learning. This study also can be used as a reference to the management faculty in students’ academic achievement problems saw athletes who is undergoing study session in in Higher Education Institution in Malaysia. In addition, as parties to monitor and coordinate the Sports Division to make this study as a guide in helping student-athletes in improving academic achievement towards empowering human capital quality and balanced academic achievement and involvement in the field of sports.
References 1. Rozali, M.Z., Puteh, S., Yunus, F.A.N., Khan, T., Khan, A.: Academic enhancement support for student-athlete in Malaysia public universities. Adv. Sci. Lett. 24(1), 223–225 (2018) 2. Shelangoski, B.L., Hambrick, M.E., Gross, J.P., Weber, J.D.: Exploring the role of educational institutions in student-athlete community engagement, 17–42 (2014) 3. Carodine, K., Almond, K.F., Gratto, K.K.: College student athlete success both in and out of the classroom. New Dir. Stud. Serv. 2001(93), 19–33 (2001) 4. Sack, A.: College sport and the student athlete. J. Sport Soc. Issues 11, 31–48 (1988) 5. Yusof, A., Chuan, C.C., Shah, P.M.: Academic achievement and sports involvement of Malaysian university athletes. Procedia Soc. Behav. Sci. 106, 273–281 (2013)
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6. Alder, P., Alder, P.: From idealism to pragmatic detachment: the academic performance of college athletes. Sociol. Educ. 58(4), 241–250 (1985) 7. Beamon, K., Bell, P.A.: Academics versus athletics: an examination of the effects of background and socialization on African American male student athletes. Soc. Sci. J. 43(3), 393–403 (2006) 8. Miller, P.S., Kerr, G.: The athletic, academic and social experiences of intercollegiate student-athletes. J. Sport Behav. 25(4), 346 (2002) 9. Tudor, M.L.: Predicting Student Athletes’ Motivation towards Academics and Athletics (2014) 10. Yelk, T.: Non-cognitive factors affecting student athlete academic performance (2013) 11. Diersen, B.A.: Student-Athlete or Athlete Student (2005) 12. Broughton, E., Neyer, M.: Advising and counseling student athletes. New Dir. Stud. Serv. 2001(93), 47–53 (2001) 13. Jones, H., Twiss, B.L.: Forecasting Technology for Planning Decision. Macmillan, New York (1978) 14. Mohd Jamil, M.R., Siraj, S., Hussin, Z., Mat Noh, N., Sapar, A.: Pengenalan Asas Keadah Fuzzy Delphi Dalam Penyelidikan Rekabentuk Pembangunan. Minda Intelek Agency, Bangi Selangor (2014) 15. Ismail, A., Hassan, R., Masek, A.: Generating elements of Supervisory Input Support via Exploratory Factor Analysis for effective supervision in Engineering Education. In: 2014 IEEE 6th Conference on Engineering Education (ICEED 2014), art. no. 7194686, pp. 46–50 (2014)
A Review of Pathways Towards Expert Performance on Elite Youth Athletes Mohd Faridz Ahmad1(&), Jeffrey Low Fook Lee2, and Ali Md Nadzalan2 1
2
Faculty of Sports Science and Recreation, Universiti Teknologi MARA, Perlis Branch, Arau, Malaysia [email protected] Faculty of Sports Science and Coaching, Universiti Pendidikan Sultan Idris, Tanjong Malim, Malaysia
Abstract. The objective of this paper was to review research publications related to the developmental pathways of elite youth athletes in sport activities. The method that had been used was PRISMA statement. Articles from Scopus database were obtained from 1956 until 2019. The key words that had been used were “deliberate play”, “deliberate practice”, “Developmental Model of Sport Participation”, “early diversification”, “early specialization” and “expertise”. The finding showed that there was total number of 10330 articles from all countries and had been stratified by following the scopes of terms of sport and athlete, duplicating journals and non-related journals. The additional criteria were the journals focusing on developmental and the language was written in English only. A number of 15 related journals had selected in this study. This review demonstrated that both pathways either by specialization or diversification can lead to the elite performance level. However, future studies need to investigate the training activities of this elite performers during their involvement at elite level. Keywords: Deliberate play Deliberate practice Early diversification Early specialization Expertise
1 Introduction Developing a sport athlete requires the implementation of good discipline, hard work and commitment towards the athlete related sport. To our knowledge, elite athlete had been developing in several and specific pathways before they achieve the expert performance. In a broader perspective, one of the elements in developing an elite athlete is the activities and pathway that they engaged in during their childhood period. These are divided into two namely specialization and diversification pathway (Ford et al. 2016) which based on the Developmental Model of Sport Participation (DMSP) (see Fig. 1) (Côté et al. 2007; Côté and Vierimaa, 2014). In the DMSP model, the early specialization pathway and the involvement in only one sport from the early age of participation (deliberate practice) is originating from the deliberate practice framework and the relationship occur between deliberate practices © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 189–198, 2020. https://doi.org/10.1007/978-981-15-3270-2_20
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activities that engaged in with the primary purpose for enhancing performance (Ericsson et al. 1993). Other than that, it also can be known as early age involvement in a single sport which often referred as ‘10-year rule” (can also be known as minimum 10,000 h or 10 years) when it deliberately focus on training and development (Simon and Chase 1973) before achieving elite performers. In addition, athlete will spend more hours in deliberate practice (involvement in structured training such as hours in competition and coach-led practice), low amount in deliberate play (involvement in unstructured training such as hours in peers-led practice and individual practice) (Low et al. 2017) and engagement in a training for single sport only (Ford et al. 2016). In line with that, the activity in soccer during the sampling years had been highlighted when majority of successful players engage early in soccer and find a balance percentage between sport-specific deliberate practice with participation in sport specific play as in refer to the DMSP model (Meylan et al. 2014). In other point of view, the DMSP also showed that the elite athlete can be related to second “sampling and play” pathway which commonly known as early diversification pathway. Through this pathway athletes have to undergo three phases of years that are sampling years between 6–11 years old, specializing years (from 12–14 years old) and investment years (from 15–18 years old) before they reach elite level. During sampling years athlete will spend more hours on deliberate play, less hours in deliberate practice and play activities with additional of multiples sports involvement during childhood period then later specialization in adolescence (Ford et al. 2016). Moving into the specializing years, the engagement in deliberate play and practice is similar while participation in other sports reduced. Lastly at the investment years phase, athletes will start to engage more in deliberate practice, a lesser amount in deliberate play and focusing only in single sport. However, in the early specialization pathway, athlete’s physical wellness and their enjoyment towards the particular sports tend to reduce. In the early specialization pathway, athlete’s physical wellness and their enjoyment towards the particular sports tend to reduce. However, these two aspects would enhance in the early diversification pathway. The debate is still continues on determining which pathway is the best in developing the elite athlete. Ericsson et al. (1993) mentioned that, deliberate practice led to focus on practice/training which directly gives an impact towards the development of expert performance and should be set as the benchmark to improve the performance. Study by Low et al. (2017) founded that national youth and state badminton players and elite youth swimmers (Tan and Low, 2014) confirm to follow early specialization pathway. In line with that, study by Ford et al. (2012) on elite under-16 soccer players from Brazil, England, France, Ghana, Mexico, Portugal and Sweden also tend to follow early specialization pathway. In contrast, study by Coutinho et al. (2016a and b) towards 18 volleyball clubs in Portugal tend to follow early diversification where they involve and participate in various types of sports during their early age. In addition, an early diversification pathway with different sports participation and the assumption of transferring the skill between sports was found to make no difference to the success rate after reaching the elite level (Ford and Williams 2008; Ford et al. 2009a; Ford et al. 2009b). Other than that, this “vice-versa” pathway is involving the sampling of different sports and play-based sporting activities during their early age and later specialization (Ericsson et al. 1993) and thought to take over the negative consequences
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that associated with specialization age, such as injury, burnout, drop-out and a general decrement in well-being (Côté et al. 2007). Therefore, the aim of this study is to review the research publications related to the developmental pathways and to identify which pathway that commonly used by elite youth athletes in sport activities in order to be expert performers.
Fig. 1. The Developmental Model of Sport Participation (DMSP) adopted from Côté et al. (2007); Côté and Vierimaa (2014)
2 Method The data collection and data analysis procedure adhered to the requirements in the PRISMA statement (Preferred Reporting Items for Systematic Reviews and MetaAnalyses (Moher et al. 2009; Coutinho et al. 2016a and b). Database searches were conducted in Scopus database only. All the databases were searched by using the keywords from Coutinho et al. (2016a and b). The keywords are “deliberate play”, “deliberate practice”, “Developmental Model of Sport Participation”, “early diversification”, “early specialization” and “expertise” and the search had been restricted to the scope of terms in several scientific fields that are ‘sport’ and ‘athlete’ in order to reduce and specify the results as been used in Coutinho et al. (2016a and b). A search for relevant articles was also performed from the lists of reference from the selected publications. This study also went through the reference lists in these publications in order to
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find the other related articles for this review. Other than that, by following the review by Coutinho et al. (2016a and b), the criteria that have been included in this study review were as follows: (1) the article had to focus either on developmental activities such as athlete, talent and pathways, athlete development models or learning activities in sports field only and (2) the articles should be written in English language only. In addition, there was no restriction regarding the study design or the publication year. Therefore, after taking into account both of these inclusion and exclusion criteria, 31 related articles were found. Figure 2 shows the flow chart for articles selection. This study records and identified the journals through database from Scopus only. Then, by referring to the keywords from Coutinho et al. (2016a and b) which were athlete and sport, this study removed any non-related articles. In addition, this study also removed the duplicate record and rejected the non-related articles with a reason. Lastly, this study also examined the findings and determined the structure of this review article.
Fig. 2. Flow diagram of the literature review search.
3 Result The result showed that (refer to Fig. 2) after the process of articles selection, only 15 articles were being included in this study. The details are shown in Fig. 3 where 12 articles were following early specialization (6) and early diversification (6) while another 3 studies were following both. Therefore, the major finding of this study is that elite performers went through both early specialization and diversification.
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7 6
6
6
Early specialization
Early diversification
5 4 3
3
2 1 0 Following both
Fig. 3. The pathways
According to DMSP model, there are two primary pathways toward sports expertise that are (1) early specialization - which focus on single sport from an early age of participation and (2) early diversification where it involves the participation in different types of sports and play-based sporting activities during early age (Ford et al. 2016; Hendry et al. 2019). A review by Baker and Young (2014) highlighted that expert athletes accumulate more deliberate practice as compare to less-experts throughout their career, either less than 4000 h for field hockey (Baker et al. 2003) or over than 18,000 h in gymnastics (Law et al. 2007). Furthermore in English Youth Soccer Academies, soccer players tend to dedicate more than 10 years and invest an average a total of 7000 h in soccer specific training which specifically designed to achieve elite performers and also enhance performance beginning at the age of 16 years old (Ward et al. 2004). In other view, athletes’ experience can be measured based on 3 elements namely age milestones, sport related activities (hours spend on competition, training with coaches, self-training and training with their colleagues) and also duration time spent in other sports activities. The finding of this study was in line with the previous study where the result by Voigt and Hohmann (2016) showed that their findings support both pathways as being described in the DMSP model. Other than that, the review by Coutinho et al. (2016a and b) determines that early specialization is not the only pathway to reach expertise but early diversification also can lead to elite performance. It had been supported by Zibung and Concelmann (2013) that special effort is required already in childhood age and commitment to other sports can also promote later top-level performance.
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Early Specialization Pathway Towards Elite Level
However, there are several studies that showed elite performers tend to follow the early specialization pathway only. This pathway focuses on specific deliberate practice in a single sport from childhood until adolescent (Macnamara et al. 2016; Macnamara et al. 2014), early participation on specific sport (normally during early to middle childhood) and no participation in other sports (or less participation) (Moesch et al. 2011). Therefore, in order to achieve expert performers, the athletes are expected to engage about 10 000 h of practice (or 10 years rule) with their specific sports participation (MacMahon et al. 2007; Philips et al. 2013). Beginning with the study by Erikstad et al. (2018), the findings showed that high level players tend to be selected into the national teams, involving more practice hours with peers and adult during childhood compared to the players who are having low level of self-regulation. In line with that, study by Drake and Breslin (2017) showed that high performing players accumulated more hours in total training session, competition (match play) and session that led by coaches. Furthermore, match play and practices that are led by coaches become the most influential and attractive factors in developing the perceptual cognitive performance. Other than that, soccer players aged under-16 years from Brazil, England, France, Ghana, Mexico, Portugal and Sweden showed minor differences between countries, but the developmental activities of the players still followed the specialization pathways, rather than early diversification (Ford et al. 2012). Likewise, another study by Low et al. (2017) highlighted that further examination on accumulation hours in structured and unstructured badminton practice activities showed almost similar forms in involvement of those activities with more emphasis on structured practice from the starting of the career even the participants’ type and amount of badminton-related practice activities showed that national players achieved some badminton performance milestones later compared to state players. This directly showed that both the national youth and state badminton players in Malaysia have follow the early specialization pathway. Apart from that, a study from Forsman et al. (2016) towards Finnish athletes clearly mentioned the importance and benefits of early involvement in sport and sport-specific play and practice during childhood in the developing the youth team athletes. In other point of view, Wall and Côté (2007) highlighted that ice hockey players who dropped out earlier from the sport had begunoff the training earlier than the athletes who continued their participation. In line with that, study by Noble and Chapman (2018) also stated that elite African marathoners achieve a greater level of performance at younger ages than their non-African counterparts. This directly indicates that early specialization training routines may have an effect towards long-term development of expert performance as being supported by Güllich and Emrich (2014). 3.2
Early Diversification Pathway Towards Elite Level
In other point of view, early diversification pathways also can lead to a top performance in athletes. The early diversification pathway indicates that the first years of sport involvement had been characterized by the participation in different sports and
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spending more hours in play-like practice which focuses less amount of time on deliberate practice activities (Moesch et al. 2011) and requires athletes to go through the three stages of years (Gucciardi 2009) with both the ratio between free play to deliberate practice and the involvement in multiple sports changing as a function of age (Côté 1999; Voigt and Hohmnn 2016). Based on the previous finding, the expert performers also can be achieved early diversification pathway (Côté et al. 2007). It was also being supported by Gűllich (2017) where the international medalists’ followed the early diversified practice and learning as it being discussed relative to the expansion of youngsters’ potential for future long-term learning. In addition, the general assumption mentioned that the talented athletes can also benefit from such a transfer between their various types of sports involvement (Williams and Ford 2008). In line with that, Baker et al. (2003) had support this view by stating that a transfer of learning can be occurs between one sport to another that also include physically and cognitive abilities. Apart from that, evidence shows that the diversification pathway is a more profound process in becoming an athlete. Beginning from study by Fraser-Thomas et al. (2008) showed that throughout the development, dropout swimmers were tend to involved less in extra-curricular activities, less in unstructured swimming play and received less face to face coaching. In addition, dropout swimmers had reached several developmental milestones earlier when compared to engaged swimmers. Then, study by Gűllich (2017) found that early diversification practice and learning experiences are relative to the youngsters’ potential expansion for long-term learning in the future. For elite athletes, the interaction between sport-specific practices with early participation in other sports mostly indicates a long-term attainment of international senior medals. In addition, Baker and Coté (2006) state that involvement during sampling years may experience more fun and enjoyment, having low frequency of dropping out and developing low risk of injuries compare to their peers that specialized during early age which indirectly can contribute to the attainment at high level performance in an adult years. Lidor and Lavyan (2002) also found that elite athletes who involve in different sports during their early participation tend to complete more training hours when they reached their peak performance and this indicated that they managed to accumulate enough hours to perform at the highest level even though they had start late. In line with that, study by Hayman et al. (2014) found that, the journey of golfers from pre- to elite adolescent golfing status were following the early diversification as they moving from diversified training to an increasingly focused on domain sport. In addition, study on Australian Track and Field athletes (refer to Olympic and World Championship athletes) showed that most of them confirm to follow the early diversification pathway and did not focus on the main senior event, and were not ready to involved in specialized intense training until the end of the investment stage (Huxley et al. 2018). Another study by Huxley et al. (2017) found that elite senior Australian Track and Field athletes continued to involve in different sports throughout their development until their adolescent years. This showed that the athletes who follow the diversification pathway rather than specialization also can lead to a greater success at their sporting
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careers. Another study stated that DMSP model and its related articles have received sufficient support from research in the last 15 years to warrant strong recommendations regarding the role that early diversification and deliberate play have in the development of an integrated sport system that value athletes’ performance, mass participation and personal development through sport (Côté and Vierimaa 2014)
4 Conclusion In conclusion, the review of this study is in line with the previous study by Voigt and Hohmann (2016) where to achieve expert performance, elite athlete can be developed in two primary pathways which are either by early specialization or early diversification. Despite the endless argument on which pathways are best in developing elite performers, both are still being used. Therefore, the major finding of this review indicates that both pathway either by early specialization or early diversification can lead to develop elite performers. As recommendation for future research study, this study suggests to investigate the training activities of these elite performers during their involvement at elite level. Funding. The author(s) declared that there were no scholarships or grant funding for this study.
References Baker, J., Young, B.W.: 20 years later: deliberate practice and the development of expertise in sport. Int. Rev. Sport Exerc. Psychol. 7, 135–157 (2014) Baker, J., Côté, J., Abernethy, B.: Sport specific training, deliberate practice and the development of expertise in team ball sports. J. Appl. Sport Psychol. 15, 12–25 (2003) Baker, J., Côté, J.: Shifting training requirements during athlete development: the relationship among deliberate practice, deliberate play and other involvement in the acquisition of sport expertise. In: Hackford, D., Tenenbaum, G. (eds.) Essential Processes for Attaining Peak Performance, pp. 92–109. Meyer and Meyer, Aachen (2006) Côté, J.: The influence of the family in the development of talent in sport. Sport Psychol. 13(4), 395–417 (1999) Côté, J., Vierimaa, M.: The developmental model of sport participation: 15 years after its first conceptualization. Sci. Sports 29S, S63–S69 (2014) Côté, J., Baker, J., Abernethy, B.: Practice and play in the development of sport expertise. In: Tenenbaum, G., Eklund, E.C. (eds.) Handbook of Sport Psychology, 3rd edn., pp. 184–202. John Wiley and Sons, Inc., Hoboken (2007) Coutinho, P., Mesquita, I., Fonseca, A.M.: Talent development in sport: a critical review of pathways to expert performance. Int. J. Sports Sci. Coaching 11(2), 279–293 (2016a) Coutinho, P., Mesquita, I., Davids, K., Fonseca, A.M., Côté, J.: How structured and unstructured sport activities aid the development of expertise in volleyball players. Psychol. Sport Exerc. 25, 51–59 (2016b) Drake, D., Breslin, G.: Developmental activities and the acquisition of perceptual-cognitive expertise in international field hockey players. Int. J. Sports Sci. Coaching, 1–7 (2017) Ericsson, K.A., Krampe, R.T., Tesch-Römer, C.: The role of deliberate practice in the acquisition of expert performance. Psychol. Rev. 100, 363–406 (1993)
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Erikstad, M.K., Høigaard, R., Johansen, B.T., Kandala, N.B., Haugen, T.: Childhood football play and practice in relation to self-regulation and national team selection; a study of Norwegian elite youth players. J. Sports Sci., 1–7 (2018) Ford, P., Williams, A.M.: The effect of participation in gaelic football on the development of irish professional soccer players. J. Sport Exerc. Psychol. 30(6), 709–722 (2008) Ford, P.R., Broadbent, D.P., Alder, D., Causer, J.: Developmental and Professional Activities of Elite Badminton Players. Liverpool John Moores University, Liverpool (2016) Ford, P.R., Carling, C., Garces, M., Marques, M., Miguel, C., Farrant, A., Stenling, A., Moreno, J., Le Gall, F., Holmström, S., Salmela, J.H., Williams, A.M.: The developmental activities of elite soccer players aged under-16 years from Brazil, England, France, Ghana, Mexico, Portugal and Sweden. J. Sports Sci. 30(15), 1653–1663 (2012) Ford, P., Le Gall, F., Carling, C., Williams, A.M.: A cross-cultural comparison of the participation histories of English and French elite youth soccer players. In: Reilly, T., Korkusuz, F. (eds.) Science and Football VI, pp. 138–142. Routledge, London (2009a) Ford, P., Ward, P., Hodges, N., Williams, A.M.: The Role of deliberate practice and play in career progression in sport: the early engagement hypothesis. High Ability Stud. 20(1), 65–75 (2009b) Forsman, H., Blomqvist, M., Davids, K., Konttinen, N., Liukkonen, J.: The role of sport-specific play and practice during childhood in the development of adolescent Finnish team sport athletes. Int. J. Sports Sci. Coaching 11(1), 69–77 (2016) Fraser-Thomas, J., Côté, J., Deakin, J.: Examining adolescent sport dropout and prolonged engagement from a developmental perspective. J. Appl. Sport Psychol. 20, 318–333 (2008) Gucciardi, D.F.: Do developmental differences in mental toughness exist between specialized and invested Australian footballers? Pers. Individ. Differ. 47, 985–989 (2009) Güllich, A., Emrich, E.: Considering long-term sustainability in the development of world class success. Eur. J. Sport Sci. 14(1), S383–S397 (2014) Gűllich, A.: International medallists’ and non-medallists’ developmental sport activities – a matched-pairs analysis. J. Sports Sci. 35(23), 2281–2288 (2017) Hayman, R.J., Borkoles, E., Taylor, J.A., Hemmings, B., Polman, R.: From pre-elite to elite: the pathway travelled by adolescent golfers. Int. J. Sports Sci. Coaching 9(4), 959–974 (2014) Hendry, D.T., Crocker, P.R.E., Williams, A.M., Hodges, N.J.: Tracking and comparing selfdetermined motivation in elite youth soccer: influence of developmental activities, age, and skill. Front. Psychol. 10(304), 1–10 (2019) Huxley, D.J., O’Connor, D., Bennie, A.: Olympic and World Championship track and field athletes’ experiences during the specializing and investment stages of development: a qualitative study with Australian male and female representatives. Qual. Res. Sport Exerc. Health 10(2), 256–272 (2018) Huxley, D.J., O’Connor, D., Larkin, P.: The pathway to the top: key factors and influences in the development of Australian Olympic and World Championship Track and Field athletes. Int. J. Sports Sci Coaching 12(2), 1–12 (2017) Law, M.P., Côté, J., Ericsson, K.A.: Characteristics of expert development in rhythmic gymnastics: a retrospective study. Int. J. Exerc. Sport Psychol. 5, 82–103 (2007) Lidor, R., Lavyan, N.Z.: A retrospective picture of early sport experiences among elite and nearelite Israeli athletes: developmental and psychological perspectives. Int. J. Sport Psychol. 33 (3), 269–289 (2002) Low, J.F.L., Mohamad, N.I., Ong, K.B., Aziz, S.A., Abdullah, M.R., Maliki, A.B.H.M.: The developmental pathways of Malaysian elite youth badminton players. J. Fundam. Appl. Sci. 9 (2S), 842–857 (2017) MacMahon, C., Helsen, W.F., Starkes, J.L., Weston, M.: Decision-making skills and deliberate practice in elite association football referees. J. Sports Sci. 25(1), 65–78 (2007)
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The Relationship Between Organizational Commitment and Internal Service Quality Among the Staff in Majlis Sukan Negeri-negeri in Malaysia Phylicia Phoa Siew Ching(&), Mohamad Nizam Nazarudin, and Pathmanathan K. Suppiah Faculty of Psychology and Education, University Malaysia Sabah, Kota Kinabalu, Malaysia [email protected]
Abstract. The objective of this study is to investigate the relationship between organizational commitment and internal service quality among the staff in Majlis Sukan Negeri-negeri in Malaysia. The respondents of this study were selected using multi-stage sampling method. 155 staff in Majlis Sukan Negeri-negeri in Malaysia were selected for this research purpose. This study is a nonexperimental research using questionnaire as the instrument. The data were analyzed using Statistical Package for Social Sciences (SPSS) version 20. The data obtained were analyzed descriptively (mean, standard deviation, and percentage). While for inferential analysis, parametric statistic tests were used (t-test, One-way ANOVA, Pearson correlation and multiple regression). The study found that the mean score for organizational commitment and internal service quality were at a high level. The result also showed that organizational commitment was not found to have significant positive relationship with internal service quality. The findings of this study can assist the human resources to understand the elements that will affect the internal service quality in an organization. This study could make an important contribution to extant research in sports management and organizational behavior to improve how staff committed to their organizations. Keywords: Organizational commitment Sukan Negeri
Internal service quality Majlis
1 Introduction Most organizations will compete to provide high quality services to enhance their organization’s performance (Porsoltani and Iraji 2012). Internal services refer to services rendered to employees while services rendered to customers are known as external services. Consistent service is provided to meet consumer expectations (Ghorbani 2014). Before focusing on external markets and customers, an organization should focus themselves on internal markets and employees as internal customers (Barnes and © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 199–205, 2020. https://doi.org/10.1007/978-981-15-3270-2_21
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Morris 2000). Intra-organizational concerns can have an impact on internal and external customer satisfaction that will likely ensure the success of an organization. Internal services are also elements that assist in achieving high quality external services. Therefore, the quality of this internal service needs to be examined in sports organization (Amirtash and Mozaf-fari 2012). Frederick and Mukesh (2001) explain the quality of the internal services is the internal environment based on the awareness to provide support among employees and support staff including management and others in the provision of support services. The concept of the quality of internal affairs in this study is characterized by the attitude of one another and the way individuals serve each other in an organization. According to Large and Konig (2009), the quality of internal services is a prerequisite for the company’s overall performance. The quality of this internal service is a clear description of the work to increase staff awareness of quality issues, productivity, customer satisfaction and trust in the services of an organization (Gotzami and Tsiotras 2002). Therefore, this aspect needs to be emphasized by an organization that emphasizes on the quality of service as it is believed that the quality of internal services is capable of enhancing the company’s internal operations and the quality of communication for both internal and external customers. Hallowell et al. (1996) suggest that the quality of internal services is closely related to the quality of customer service. Chelladuraie (2003) also noted that internal services offered to employees can also influence the quality of services offered to external customers, thus significantly contributing to organizational performance. Hence, human resource management needs to have a sustainable strategy to produce excellent employees as it refers to the way and organization used by the organization to manage and control activities related to human resources in the organization to be aligned and achieve organizational goals (Faridahwati et al. 2006). Among other factors that encourage researcher to study this variable are, Ramseook-Munhurrun et al. (2009) in his study found that most public services failed to meet customer expectations and requirements. Additionally, Di Xie (2005) also pointed out that in most cases, sports organizations are only trying to assess the quality of services from the perspective of external customers only but do not look at the quality of internal services and interactions among employees. This situation is particularly alarming, especially for public services that provide services to customers because poor service quality affects customers’ trust and external customer numbers and will indirectly interfere with the performance of such an organization. According to Di Xie (2005), previous study also mostly only tested on the relationship between organizational commitment and turnover but there is less research that look into the relationship between organizational commitment with the employee’s work-related behaviors. Studies conducted by Boshoff and Allen (2000) shows that the organizational commitment of an employee can help in determining the level of service quality delivered to the customers. This is because previous study found that there is a positive relationship between organizational commitment and customer perceptions of
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service quality (Di xie 2005; Pedrick 1998). Organizations that have strong cooperative internal work environment are also likely to have higher levels of service orientation (Di Xie 2005; Lytle 1994). Based on these problems, it has led researchers to research and conduct research to explain the relationships and factors that influence the quality of internal services in the State Sports Council organization so that the quality and performance of the organization can be enhanced and the quality of the sports organization is at a better level. The objective of this study is identify the level of organizational commitment and internal service quality of staff at Majlis Sukan Negeri-negeri in Malaysia. Next is to identify the relationship of organizational commitment and internal service quality at Majlis Sukan Negeri-negeri in Malaysia. Ho1: There is no significant relationship between organizational commitment and the internal service quality in Majlis Sukan Negeri-negeri.
2 Methodology This study is a quantitative non-experimental study using questionnaire instrument. The questionnaire used was Organizational Commitment Scale (Meyer et al. 1993) and Internal Service quality scale (INTQUAL) by Caruana and Pitt (1997 modified by Cook 2004). This study was conducted at Majlis Sukan Negeri-negeri in Malaysia with a population size of study of 249 staff members of the State Sports Council in Malaysia who graduated S19 and above only. In order to meet the random sampling purpose of this group, the Krejcie and Morgan (1970) formula has been used as the basis for viewing the sample size through the total number of surveys. According to the formula, the sample size is within the range of 148–152 respondents. The number of population that researchers use is 155 people.
3 Results 3.1
Organizational Commitment and Internal Service Quality of the Staff at Majlis Sukan Negeri-negeri in Malaysia
Table 1 shows the analysis and brief descriptions of respondent demographics. Respondents’ demographics in this study involved several aspects such as gender, age and years of working experience.
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Table 1. The demographic distribution of the respondents of the State Council Sports Council staff grades S19 and above. Characteristic Gender Women Man Age 30 years old and below 31–40 years old 41–50 years old 51 years old and above Working experiences Less than 1 years 1–5 years 5–10 years 10 years and above
Frequency Percentage (%) 75 80
48.4% 51.6%
70 47 31 7
45.2% 30.3% 20.0% 4.5%
26 45 51 33
16.8% 29.0% 32.9% 21.3%
Table 2 shows the results of the min score for job satisfaction (min = 5.80) and the quality of internal service (min = 5.91) at the State Sports Council in Malaysia. This mean score shows that it is at a high level. Table 2. Results of the mean score for each study variable N Minimum Maximum Mean Std. deviation MinA 155 5.14 6.48 5.8372 .31150 MinD 155 5.00 6.50 5.8047 .30791 Valid N (listwise) 155
3.2
Relationship Between Organization Commitment with Internal Service Quality
Table 3 shows Pearson Correlation Coefficient of relationship between organizational commitment with internal service quality is r = −.053. This shows that there is a very strong and very significant positive relationship between job satisfaction and the quality of internal affairs of staff of the State Sports Council in Malaysia. The Pearson Correlation Test Result is, r (155) = −.053, p < .01. Therefore, Ho1, no significant relationship between organizational commitment with the quality of internal services is accepted.
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Table 3. Relationships between organizational learning culture and the quality of internal services
Internal service quality
Pearson correlation Sig. (2-tailed) N
Internal service quality 1
Organizational commitment −053
155
.510 155
4 Discussion Descriptive statistical findings show that organizational commitment and internal services quality each have a high level. Through this study, it was found that the level of organizational commitment and internal quality service was at a high level. The results of the analysis of the relationship between the organizational commitment and the quality of the internal service showed that there was no significant relationship. This may be influenced by the smaller employment sector resulting in the fact that most staff regardless of whether men or women do not have the opportunity to choose jobs that are in line with their field so that the staff does not have deep feelings and sense of responsibility (normative commitment) to an organization to engage in an organization (affective commitment). This means that staff in the organization may not be given assignments according to their interests but rather the skills they have. Furthermore, it is also found that staff in the organization of the State Sports Council had a constant commitment despite being relatively weak but this staff may work in the State Sports Council’s organization for considering losses if they leave the organization and to secure permanent jobs to secure their future. Even though there is strong evidence that the development of internal service quality is important in today’s modern organization, there is still very little research done to study the relationship between the quality of internal services and organizational commitment and the average review results have varying insights. In this study, the findings show that there is no significant one-way relationship between organizational commitment with internal service quality (r = −0.053, p = 0.51). This condition can be seen in the previous study conducted by Gremler et al. (1994); Hallowell et al. (1996); Heskett et al. (1994) which in its study shows that the quality of internal services is an important driver of organizational commitment factors. Another study conducted by Bai et al. (2006); Paulin et al. (2006) found that service quality and job satisfaction were the variables that influenced organizational commitment. Testa (2001) study which looked at the relationship between organizational commitment, job satisfaction and internal service quality also found that organizational commitment was the moderator of job satisfaction and the quality of internal services. It is clear that variables studied have the opposite of which the organizational commitment does not affect the quality of internal services.
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5 Conclusion In conclusion, the aspect of organizational commitment amongst the staff should be studied in more detail as this aspect is one of the psychological aspects that can influence the improvement of the internal service quality of an organization. Organizational commitment is believed to have an association with the behavior of an individual in an organization. Therefore, in order to improve the organizational commitment of staff work in the Majlis Sukan Negeri, organizational management should pay attention to the aspects that will influence the organizational commitment in order to make improvements to produce a more positive level of relationship between employee satisfaction and the quality of internal services within such an organization to contribute to the long-term profitability and success of an organization.
References Amirtash, A.M., Mozaffari, S.A.A.B.N.: The relationship between organizational learning culture and job satisfaction and Internal service quality in sport organizations in Iran. Eur. J. Exp. Biol. 4(2), 1220–1225 (2012) Barnes, B.R., Morris, D.S.: Revising quality awareness through internal marketing: an exploratory study among French and English medium-sized enterprise. Total Qual. Manag. 11, 473–483 (2000) Bai, B., Brewer, K.P., Sammons, G., Swerdlow, S.: Job satisfaction, organizational commitment, and internal service quality: a case study of Las Vegas hotel/casino industry. J. Hum. Resour. Hosp. Tour. 5(2), 37–54 (2006) Boshoff, C., Allen, J.: The influence of selected antecedents on frontline staff perceptions of service recovery performance. Int. J. Serv. Ind. Manag. 11(1), 63–90 (2000) Caruana, A., Pitt, L.: INTQUAL – an internal measure of service quality and the link between service quality and business performance. Eur. J. Mark. 31(8), 604–616 (1997) Chelladuraie, P.: Motivation performance of sport organization staff. J. Sport Manag. 18, 73–82 (2003) Cook, S.: Measuring Customer Service Effectiveness. Gower Publishing Company, Burlington (2004) Di Xie, M.S.: Exploring organizational learning culture, job satisfaction motivation to learn, organizational commitment and internal service quality in a sport organizational. The Ohio State University (2005) Faridahwati, M.S.: Organisational misbehavior. Akademika 69, 57–82 (2006) Frederick, A.F., Mukesh, K.: Service quality between internal customers and internal suppliers in an international airline. Int. J. Qual. Reliab. Manag. 18(4), 371–386 (2001) Ghorbani, A., Yarimoglu, E.K.: E-Service Marketing. In: Ghorbani, A. (ed.) Marketing in the Cyber Era: Strategies and Emerging Trends, pp. 1–8. IGI Global, Pennsylvania (2014) Gotzami, K.D., Tsiotras, G.D.: The true motives behind ISO 9000 Certification: their effect on the overall certification benefits and the long term contribution towards TQM. Int. J. Qual. Reliab. Manag. 19(2), 151–169 (2002) Gremler, D., Bitner, M.J., Evans, K.: The internal service encounter. Int. J. Serv. Ind. Manag. 5(2), 34–56 (1994) Hallowell, R., Schlesinger, L.A., Zornitsky, J.: Human Resource Planning 19(2), 20–31 (1996)
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Heskett, J.L., Jones, T.O., Loveman, G.W., Sasser Jr., W.E., Schlesinger, L.A.: Putting the service-profit chain to work. Harv. Bus. Rev. 72(2), 164–170 (1994) Krejcie, V.R., Morgan, W.D.: Determining sample size for research activities. Educ. Psychol. Meas. 30, 607–610 (1970). University of Minnesota, Duluth Large, R.O., Konig, T.: A gap model of purchasing’s internal service quality: Concept, case study and internal survey. J. Purchasing Supply Manag. 15, 25–32 (2009) Lytle, R.S.: Service orientation, market orientation, and performance: An organizational culture perspective. Unpublished dissertation. Arizona State University (1994) Meyer, J.P., Allen, N.J., Smith, C.A.: Commitment to organizations and occupations: extension and test of a three-component conceptualization. J. Appl. Psychol. 78, 538–551 (1993) Paulin, M., Ferguson, R.J., Bergeron, J.: Service climate and organizational commitment: the importance of customer linkages. J. Bus. Res. 59(8), 906–915 (2006) Pedrick, D.L.: The influence of organizational climate on employee, customer and firm performance. Unpublished dissertation. The University of Memphis (1998) Porsoltani, H., Iraji, R.: The relation between Organizational socialization and Job Satisfaction in Khorasn Razavimain Physical Education office employees in 2010. J. Sport Manag. Motor Behav. 15, 79–96 (2012) Ramseook-Munhurrun, P., Naidoo, P., Lukea-Bhiwajee, S.D.: Employee perceptions of service quality in a call centre. Manag. Serv. Qual. Int. J. 19(5), 541–557 (2009) Testa, M.R.: Organizational commitment, job satisfaction, and effort in the service environment. J. Psychol. 135(2), 226–236 (2001)
Accessibility Dimensions (Factors) of Parks and Playgrounds Ellail Ain Mohd Aznan(&), Ahmad Fikri Mohd Kassim, Nurul Hidayah Amir, Mohd Khairulanwar Md Yusof, Mohd Syafiq Miswan, and Nur Anis Fatima Amir Universiti Teknologi Mara (UiTM), Perlis, Arau, Malaysia [email protected]
Abstract. The design for each park and playgrounds was purported in contributing a healthy lifestyle among the public. The most crucial element in the designing the parks and playgrounds was the accessibility. Studies upon accessibility had been done in the previous years in determining the importance of accessibility towards the publics. Therefore, the current study aims to identify factors dimension that influence the attendance of parks and playground. Through a model developed by Wang et al. (2015), the park accessibility can be divided into five dimensions. The dimension focused in the present study are physical and social dimension. Physical dimension included number and area of parks, proximity and walkability. As for the social dimension, the items included were safety and shared activities. 120 visitors Male (n = 60) and female (n = 60) completed questionnaire pack assessing the study variables. Finding from this study indicate that both dimensions share a similar preference by the visitors. Keywords: Accessibility
Parks and playground Attendance
1 Introduction 1.1
Accessibility
In enabling a physically and socially fit society engagement in sports and recreation activities is a must. Due to the current situation most of the activities engaged in welldesigned park and playground. The accessibility to the park and playgrounds in important in assuring the attendance of the publics. Through every facility construction, the accessibility can be considered as the important factors. According to Lin et al. (2014), accessibility involves a variety of factors such as the physical of road environment, transport modes, scope of activity, personal preferences and they often included travel cost, land use mix service quality in terms of speed, frequency, comfort, parking availability, and congestion. Further, Slatten et al. (2011), propose that customers or visitors consider pleasant experiences as the core product contribution as they can take away the memories they developed during consumption. Through a model developed by Wang et al. (2015), the park accessibility can be divided into five dimensions. The dimension included were physical, transport, © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 206–212, 2020. https://doi.org/10.1007/978-981-15-3270-2_22
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knowledge, social and personal. As for this current study the physical and social dimension were focused. Physical dimension includes on two main factors such as the number/area of park and the walkability. As for the social dimension, the factors determined was safety. There are many previous researches were focusing on the physical dimensions. For example, a study from Seifried (2010), mentioned that sport and recreation facilities appear as culturally relevant artefacts and recognized as ‘sacred’ spaces because they have evolved over time to meet different political, economic, and social initiatives or preferences. In the new and globalize era, the parks and playgrounds had evolved from a simple designed facility to a high-quality facility to be accessed by the publics. Perry et al. (2018) in their study stated that, the parks were classified as either ‘neighborhood’ or ‘destination’ parks. Destination parks were defined as premier playground which people will travel to for the play opportunities they provide. With open space play, there is a large selection of play equipment which will suit a wide range of ages and abilities. These playgrounds also contain number of amenities, for example, toilets, rubbish bins and drinking fountain and are suitable of hosting large user numbers. The social dimension like the safety also contribute in the accessibility to the parks and playground. Alkhadim et al. (2018) stated that safety in the built environment is made of objective safety and subjective safety. In an organizational context, objective safety is measured through the actual number or risk of incidents or injuries occurred in an organization. Whilst, subjective safety is intangible, and it refers to the feeling or perception of being safe or unsafe within a specified period (Alkhadim et al. 2018). 1.2
Motivation of Attendance
Motivation can be used in defining a person behavior. Motivation can be defined as psychological/biological needs and wants that arouse, direct, and integrate a person’s behavior and activity (Park et al. 2008). The motivation or motives can be considered as the need for any decision making and engagement in a person’s behavior (Park et al. 2008). Different individuals engage in different behaviors because they want to satisfy different needs. By understanding the needs, the desire can be fulfilled. For park planners it is important to understand the needs of the users in determining the suitable facilities and types of accessibility to be provided (Park et al. 2008). In the United States, the visitation and attendance of visitors had increased in the 2000s. Smith et al. (2019) stated that, parks have been visited frequently which led to the high chances of risk. Annual visits to the national parks, for example, increased by 33% from 1984 to 2017 (US Department of Interior, National Park Service 2019), current visitation is over 330 million (Smith et al. 2019) the increment of visitation and attendance to park will affected the capacities that can be handled by each park. The visitation or attendance frequency and capacities will be led to the visitor health, safety, and enjoyment. A crowded area also led to greater, or more severe, environmental disturbances on-site as well as high risk of injury (Smith et al. 2019). Environmental settings have multiple physical, cultural, and social constructs that influence health behavior (Qazi 2013). Qazi (2013) stated that socioecological models also help identify opportunities that promote participation in physical activity by
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targeting either individual or combined interventions against social, physical, and policy factors that inhibit physical activity. The attendance to a park can be categorized into two main system which are the micro and macro. Microsystem refers to the setting in which the individual lives, for example, a family and a school (Qazi 2013). Macrosystem refers to the broad social or cultural context in which a person lives and includes belief systems, material resources and opportunity structures (Qazi 2013). However, by understanding the macrosystem the park planner will be able to identify the factors that leads to the frequency of park attendance and visitation (Qazi 2013). The elements of the macrosystem, which include the park and playground quality and access, may help public health researchers to develop interventions. The interventions mentioned includes improving quality of the parks and playground by having cost-saving renovation of parks that lead to the increment of physical activity at the community area (Qazi 2013).
2 Problem Statement Mehta (2013) stated that perceived safety refers to the feeling or perception of an unsafe situation that exists during an event. Studies in urban design have shown that perceived safety can be affected by the characteristic of the environment, physical condition, and configuration of spaces. Therefore, examination and controlling the physical environments as well as safety are significant. However, in the local area they are limited examination and controlling had been done for parks and playground. Even though the main reason for standards investigation is occurrence of several incidents all over the world, which is reported to be about 16,000 deaths due to various injuries as one major causes of death. Many of these situations rarely reported officially. The important preconditions are expected, including park proximity as well as attractive and motivating physical activity areas in parks, where the elderly engage in their favored physical activity. The results review by Evenson et al. (2016) and (Chow et al. 2016; Cohen et al. 2006), revealed that there is a general positive relationship between park proximity or accessibility and active park use. However, because previous studies of renovations have not used randomized design and have included few parks, conclusions on effectiveness are limited.
3 Research Methodology 3.1
Population and Sample
The related population of the participants that attending the parks and playground located in area of the study. A total of 120 samples randomly selected among the participants. Self-administered questionnaires were distributed to the community that attend the parks and playgrounds.
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Research Instrument
This study used the questionnaire. The questionnaire is divided into 3 sections which are section A to determine the demographic profile of the respondents, section B to indicate items of facility accessibility and section C to indicate the items for safety. The questionnaire was adapted and adopted from: a. Perry et al. (2018), on their studies used ‘The accessibility and usability of parks and playgrounds’ b. Wang et al. (2015) on their studies used ‘The physical and non-physical factors that influence perceived access to urban parks’ The data was collected using questionnaire with Likert Scale questions. This Likert Scale questions consisted of 43 questions categorized into ‘A’, ‘B’, and ‘C’. Section ‘A’ will consist of four question seeking to identify the demographic status, gender, participation in sport, and academic level. Section ‘B’ which consists of 19 items which focused on the physical dimension. Section ‘C’ with 19 items question which focused on social dimension. The 38 Likert Scale questions ranged from 1 until 4 (1-Strongly Disagree, 2-Disagree, 3-Agree and 4-Strongly Agree).
4 Result Table 1 indicate the frequencies of physical dimension that influence the community’s attendance at parks and playgrounds at the study area selected. The most influenced items identified were “There was adequate dustbin” (M = 3.35), “There is a rest area” (M = 3.33), “There are accessible for car parks” (M = 3.28), “The play area are fenced at a height of 1.2 m” (M = 3.23), “The main path surface is regular and even” (M = 3.07), “There is adequate lighting of the playground” (M = 3.00).
Table 1. Physical dimension influence community’s attendance at parks and playgrounds (N = 120)
There was adequate dustbin There is a rest area There are accessible for car parks The play area is fenced at a height of 1.2 m The main path surface is regular and even There is adequate lighting of the playground Overall
Percentage of frequency (%) Mean sd. Strongly Disagree disagree 3.35 .785 2.5 11.7 3.33 .613 7.5 51.7 3.28 .673 1.7 6.7 3.23 3.62 1.7 20.0
Agree Strongly agree 34.2 51.7 40.8 0 55.0 35.8 64.2 13.3
3.07
.719 4.2
10.0
60.8
25.0
3.00
.733 4.2
14.2
59.2
22.5
3.21
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Table 2 showed frequencies of social dimension that influence the community’s attendance at parks and playground. The most influenced items identified were “Good maintenance of plants in the park is a safety that should be prioritized” (M = 3.20), “The design of park amenities and recreation features promote public security and maintain user safety” (M = 3.19), “Feel safe when visiting this park” (M = 3.16), “Adequate sight lines for people” (M = 3.15), “Trees influence the safety value in this park” (M = 3.13), “Safe bicycle and pedestrian paths (M = 3.10), “I do feel safe with the vegetation condition that exists around this park” (M = 3.08), “Take off areas, landing areas and the length of the track should remain clear of any obstacles” (M = 3.04), “The lighting is suitable and sufficient to allow safe access and exit” (M = 3.01).
Table 2. Social dimension factors influence the community’s attendance at parks and playgrounds (N = 120) Percentage of frequency (%) Mean sd. Strongly Disagree Agree Strongly disagree agree Good maintenance of plants in the park 3.20 .643 .8 10.0 57.5 31.7 is a safety that should be prioritized 3.19 .639 2.5 5.0 63.3 29.2 The design of park amenities and recreation features promote public security and maintain user safety Feel safe when visiting this park 3.16 .686 1.7 11.7 55.8 30.8 Adequate sight lines for people 3.15 .575 .8 7.5 67.5 24.2 9.2 64.2 25.0 Trees influence the safety value in this 3.13 .629 1.7 park Safe bicycle and pedestrian paths 3.10 .771 4.2 12.5 52.5 30.8 I do feel safe with the vegetation 3.08 .624 .8 13.3 63.3 22.5 condition that exists around this park 3.04 .679 2.5 13.3 61.7 22.5 Take off areas, landing areas and the length of the track should remain clear of any obstacles The lighting is suitable and sufficient to 3.01 .761 4.2 15.8 55.0 25.0 allow safe access and exit Overall 3.11
5 Discussion and Conclusion Results of this study showed that community who attended parks and playgrounds were because of some facilities factors that attract their attention. The highest related facilities factor is adequate dustbin. This is proven in Table 1 which revealed that this factor obtained the highest mean score. Previous research by Ajibola et al. (2015) explain that the elements that were observed to be the most significant need such as
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lighting, dustbins, play areas, seats, jogging path, exercise stations, gazebos, signage, walkways and directional signage since the frequent users are more concerned with the services and facilities provided by parks. Next is there is a rest area. The existence of the rest area at the park will strengthen the relationship between the others. Usually parents will send their children playing in the park and while waiting for the kids to play, parents will spend their time talk to each other. This situation will lead to the accessibility of the parents to be seated comfortably while waiting for their children. The park visitors agree that the presence of the physical waiting area is important for them. Other than that, presence of accessible car park spaces are recognized facilitators for increasing physical activities and use of recreational environments. However, Perry et al. (2018) found that less than a third of the parks evaluated had accessible car parking, none of which met all the recommended dimensions for a fully accessible parking space. This finding supports the need for more accessible car parking spaces as well as modifies the existing parking spaces to meet the recommended guidelines to make them usable. Accessible car parking spaces were more commonly provided in less deprived geographical areas, and at destination parks suggesting the need for increased focus on car parking in areas of high deprivation and more local neighborhood parks. For the social dimension which incurred the safety item, good maintenance of plants in the park is a safety that should be prioritized scores the highest mean (see Table 2). The respondents characterized that vegetation as a highlight environment which familiar to physical activity for women. Most of them described the park as ‘beautiful’, ‘pretty’, ‘green’, colorful, and safe places to walk. In deference to the rural or urban park, women are more doubt of crime than men. Nowadays, there are so many crime cases reported even in the recreational park area. The park visitors agree that a good park planning with a good quality of walking area can help in increasing the secure feelings. The design of park amenities and recreation features promote public security and maintain user safety as the priority (see Table 2). The respondents might reflect with the proved of the design at the park which can secure them when they were in that park. Study by Yung et al. (2017), have provided design criteria mainly focusing on the physical and safety aspects. However, the long-term significance of this study is its contribution to the planning and design of public parks that promote social well-being of the elderly in their local areas. Additional insights derived from this study could help planners and urban designers upgrade local public parks when it comes to the design of urban renewal districts to enhance healthy ageing and aging in place. Qazi (2013) also mentioned that visitation of a park can be affected by the safety equipment and facilities provided by the park to the parents. The children can be exposed to injury and the safety of the children is related to the conditions of the equipment and facilities provided (Qazi 2013). Therefore, for the safety factor the respondents feel safe when visiting park. Sreetheran and Van den Bosch (2015) point out that females prefer to visit the park in a group as they tend to feel safe when accompanied by their husbands, other family members, where many people are engaged or at least with their dogs. Most informants did not highlight the negative experiences or factors which evoke the feeling of fear
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while they were in the park until they were probed further. Thus, through this study, the local at this study have similar preferences for both dimensions. They believe that both dimensions influence their attendance to the parks and playground. It was suggested that for future research the area could be widen so that the result may be vary.
References Chow, H.W.: Outdoor fitness equipment in parks: a qualitative study from older adults’ perceptions. BMC Public Health 13, 1216 (2013). https://doi.org/10.1186/1471-2458-131216 Cohen, D.C., Stockdale, C.R., Doyle, P.T.: Feeding an energy supplement with white clover silage improves rumen fermentation, metabolizable protein utilization, and milk production in dairy cows. Aust. J. Agric. Res. 57(4), 367–375 (2006) Evenson, K.R., Jones, S.A., Holliday, K.M., Cohen, D.A., McKenzie, T.L.: Park characteristics, use, and physical activity: a review of studies using SOPARC (System for Observing Play and Recreation in Communities). Prev. Med. 86, 153–166 (2016) Smith, J.W., Wilkins, E.J., Leung, Y.-F.: Attendance trend threaten future operations of America’s state park system. Department of Parks, Recreation and Tourism Management (2019) Lin, T., Xia, J., Robinson, T.P., Goulias, K.G., Church, R.L., Olaru, D., et al.: Spatial analysis of access to and accessibility surrounding train stations: a case study of accessibility for the elderly in Perth, Western Australia. J. Transp. Geogr. 39, 111–120 (2014). https://doi.org/10. 1016/j.jtrangeo.2014.06.022 Mehta, V.: The Street: A Quintessential Social Public Space (2013) Perry, M.A., Devan, H., Fitzgerald, H., Han, K., Liu, L.T., Rouse, J.: Accessibility and usability of parks and playgrounds (2018) Park, K.-S., Reisinger, Y., Kang, H.-J.: Visitors’ motivation for attending the south beach wine and food festival, Miami Beach, Florida. J. Travel Tour. Mark. 25(2), 161–181 (2008) Ajibola, M.O., Oyedele, F.O., Ayedun, C.A., Oni, A.S.: Examining the effects of Jabi Lake Park on property values in Jabi District, Abuja, pp. 84–95, February 2015 Qazi, H.A.: The relationship between quality of parks and playgrounds and park based activity in children. Electronic thesis and dissertation repository, 1653 (2013) Sreetheran, M.: Exploring the urban park use, preference and behaviors among the residents of Kuala Lumpur, Malaysia. Urban For. Urban Green. 25(May), 85–93 (2017) Seifried, C.S.: An ideal type for the evolution of sport facilities: analyzing professional baseball and football structures in the United States. Sport Hist. Rev. 41(1), 50–80 (2010) Slatten, T., Krogh, C., Connolley, S.: Make it memorable: customer experiences in winter amusement parks. Int. J. Cult. Tour. Hosp. Res. 5(1), 80–91 (2011). https://doi.org/10.1108/ 17506181111111780 US Department of the Interior: National park service, Natural resource stewardship and science, National park service visitor use statistics (2019). https://irma.nps.gov/Stats/reports/national. Accessed 11 Mar 2019 Wang, D., Brown, G., Liu, Y.: The physical and non-physical factors that influence perceived access to urban parks. Landsc. Urban Plan. 133, 53–66 (2015). https://doi.org/10.1016/j. landurbplan.2014.09.007 Yung, E., Ho, W., Chan, E.: Elderly satisfaction with planning and design of public parks in high density old districts: an ordered logit model. Landsc. Urban Plan. 165, 39–53 (2017). https:// doi.org/10.1016/j.landurbplan.2017.05.006
Physical Activity and Health
Influence of Individual Physical Activity on EMG Muscle Activation Pattern Maisarah Sulaiman1(&)
, Aizreena Azaman1,2
, and Azli Yahya1
1
2
School of Biomedical Engineering and Health Sciences, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru, Malaysia [email protected], [email protected], [email protected] Sport Innovation Technology Centre (SITC), Universiti Teknologi Malaysia, Johor Bahru, Malaysia
Abstract. Regular physical activity (PA) is associated with significant physiological health benefits for all individuals where various objective and subjective tools were used for evaluating PA. The aimed of this study is to access individual muscle activation and its relationship with their daily physical activity characteristics. A total of seven male subjects voluntarily participated in this study. Physical activity of each individual was derived from long, selfadministered International Physical Activity Questionnaire (IPAQ) while the muscle activation was recorded from vastus lateralis muscle using wireless electromyography (EMG) system. Each subjects are required to perform maximum voluntary contraction of knee extension exercise. Both time domain features; root mean square and frequency domain features; mean frequency, median frequency were extracted from the raw EMG signals and its relationship was compared with MET-min/week scores obtained from IPAQ using Pearson correlation analysis. Regression line was also been plotted in order to observe the EMG muscle activation pattern. Overall, root mean square value showed the best correlation between IPAQ data and EMG muscle activation data. Different muscle activation pattern can also been observed between time and frequency domain features, where time domain feature which is RMS showed decreasing trend of muscle activation with the increasing of PA. This findings suggest that overall physical activity scores were moderately correlated with some EMG features, thus further attention should be given when only relying on IPAQ to classify active or inactive individual. Keywords: Muscle activation
Physical activity Electromyography IPAQ
1 Introduction Physical activity is defined as any movement made by skeletal muscles that result in energy expenditure [1]. Regular physical activity has benefits for all individuals in all ages as its contributing to promote health, thus improving our quality of life [2, 3]. Appropriate assessment of individual PA levels are important as physical inactivity may lead to chronic and non-communicable diseases such as high blood pressure, obesity and cardiovascular disease [4–6]. Various objective and subjective tools are © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 215–222, 2020. https://doi.org/10.1007/978-981-15-3270-2_24
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used to measure physical activity where both methods have its own pros and cons. Objective measures can provide more reliable data in accessing and monitor their physical activity level in order to promote good health and active lifestyles. However, the simplest and most common approach to evaluate physical activity are via subjective measure such as self-administered based questionnaire. International Physical Activity Questionnaire (IPAQ) has been developed by a working group of public health and physical activity experts as one tools to access physical activity [3]. It available through various languages, and can be found in two forms; short and long forms where usually, long format is used when requiring more detailed information. Four sets of domain are accessed; work-related, transport-related, housework and leisure time activity. Plus, assessment for each domain are sub-divided into three intensities which are walking, moderate and vigorous intensity. This type of questionnaire is being accessed and scored based on the summation of frequency and durations for all types of activity or by expressing the intensity as MET- minutes/week. The reliability of the IPAQ is sometimes gain a lot of attention as the information obtained from the questionnaire is culture-dependent [7] and mostly influenced by the ability of respondents to recall their daily activity which leads to bias [5]. Most of the studies are comparing the reliability of IPAQ with the objective measure tool such as accelerometer. Depending on the nature of studies and subjects, some studies show that IPAQ overestimates [3, 5] physical activity as the participants obtained low level of physical activity when tested with accelerometer while some shows moderate [7] to strong [8] relationships between those two instruments. Physical activity can also be relate and strongly influenced with the muscle performance where Preto et al. stated that physically active students would have higher muscle strength and mass [2]. As in our daily life, every movement and activity that we made are mostly generated by muscle [9]. In addition, as stated by Ekris et al. our body movements can be indicated by accelerometer counts, muscle activity and heart rate [10]. By measuring electromyographic activity, detailed information regarding muscle activity can be evaluated in which it cannot be obtained through accelerometer and heart rate monitor. Muscle activity can also be considered as primary stimulus to increase energy expenditure as when it is being activated, metabolic rate of muscle will increase, thus increasing the energy expenditure [11]. However, little was known on the relationship between physical activity evaluated through IPAQ and muscle activation based on electromyography analysis. Thus, the aimed of this study was to access the muscle activation pattern in individuals with different level of physical activity by evaluating the correlation between physical activity derived from IPAQ with the muscle activation obtained from electromyography signal.
2 Method 2.1
Participants
A total of seven male subjects aged from 23 to 25 years old voluntarily participated in this study. Subjects are university students with a variety of lifestyles and background so that the data obtained are from different level of PA. Written informed consent was
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provided and signed prior to their participation in this study and none of the participants reported any musculoskeletal injury or neuromuscular disease. 2.2
Experimental Setup and Procedure
Two different measurements which involve objective and subjective tools were conducted for each participant. Firstly, participants were instructed to fill in selfadministered questionnaire which gather information regarding their daily physical activity during last 7 days prior to the test. Next, in order to access muscle activation pattern for each individual, electromyography analysis was used. The relationship between these two measurements were then evaluated using statistical analysis tools. International Physical Activity Questionnaire (IPAQ) Physical activity was accessed using long version of IPAQ based on four domain; work, transportation, housework and leisure time and three intensity level; walking, moderate and vigorous activity. Scores for total physical activity, specific domain and specific intensity level were calculated in order to categorize individual level of physical activity. The score was determined based on the total MET-minutes/week which was calculated by multiplying metabolic equivalent of task (MET) values; walking = 3.3 METs, moderate intensity = 4.0 METs, and vigorous intensity = 8.0 METs with the total duration of activities for each level as in Eq. (1). Summation of these three intensity levels yield to total physical activity score as summarized in Eq. (2). Individual physical activity level was determined as suggested by the IPAQ scoring protocol and guidelines [12]. MET - minutes/week ¼ MET level minutes/day days/week
ð1Þ
Total physical activity score ¼ Total walking MET - minutes/week þ Total moderate MET - minutes/week þ Total vigorous MET - minutes/week ð2Þ Electromyography (EMG) Muscle electrical activity was measured using Delsys Trigno™ Wireless EMG System. Skin preparation was conducted before the electrode placement where the excess hair of the targeted muscle was shaved, followed by dirt or dead skin removal using alcohol swab. Vastus lateralis muscle was chosen as it is one of the main locomotor [9, 11] and weight bearing [10] muscles which mostly used for daily physical activity. During the test, subjects were required to maximally extend their legs and hold the contraction for 30 s. The procedures were conducted using knee extensor device. Electromyography signal with the sampling rate of 2000 Hz was recorded along the testing. Raw EMG signals were processed using MATLAB software. Two main processing steps in electromyography analysis are pre-processing and feature extraction. As the main purpose of pre-processing was to remove noise and artefact, Butterworth bandpass filter was used with cut-off frequency of 20–450 Hz. Three main EMG features were extracted from the filtered signals which are time domain features such as root
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mean square (RMS) and frequency domain features such mean frequency (MNF) and median frequency (MDF). All these features are being correlated with the IPAQ scores. 2.3
Statistical Analysis
All data were analyzed using SPSS software version 23. Normality testing based on Saphiro-Wilk test was applied and data transformation was conducted for non-normally distributed variables. Pearson’s correlation coefficient, r was used to assess the relationship between physical activity level obtained by IPAQ and muscle activation from electromyography analysis. Linear regression line was also been plotted on the scattered data of IPAQ score and each EMG features in order to access the influence of individual physical activity towards muscle activation patterns.
3 Result All participants successfully complete both assessments. Demographic and anthropometric data for all subjects are as described in Table 1. The mean age for the participants was 24.14 years old in which all subjects were recruited among university students. On average, the participants were categorized in normal weight category as the mean BMI values was 20.66 kg/m2. Table 1. Participant’s characteristics Variables Mean ± standard deviation Age 24.14 ± 0.8 Weight (kg) 59.71 ± 10.77 Height (cm) 169.43 ± 5.97 Body mass index (BMI) (kg/m2) 20.66 ± 2.60
Based on the self-reported questionnaire that had been filled by all participants, it was reported that more than half of subjects (71.4%) in the present study been categorized in high physical activity level in which the total MET scores obtained was more than 3000 MET-minutes/week. Figure 1 demonstrate the mean total time spent of all participants for each domain. It showed that the participants had the highest time spent on leisure activity with 40% of the total mean score while lowest time spent are on work domain as participants only spent 4% of their time for work. In addition, participants also reported to spend most of the time on transportation as it obtained the second largest MET-min/week’s scores with 32%. The assessment of electromyography analysis had been conducted by analysing the time and frequency domain features. The time domain features that had been evaluated are root mean square (RMS) while mean frequency (MNF) and median frequency (MDF) are two of frequency domain features that had been accessed. Table 2 shows the correlation result between physical activity scores and muscle activation obtained from
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4%
40%
32%
24%
Work
TransportaƟon
Household
Leisure
Fig. 1. Average IPAQ scores for all participants by each domain
EMG data. For total physical activity, all EMG features showed low correlation with the IPAQ score. However, when focusing on the specific intensity level of physical activity such as walking, moderate and vigorous physical activity, vigorous physical activity showed the highest correlation with all EMG features compared to walking and moderate physical activity. In addition, RMS value shows the best correlation compared to both mean and median frequency. Table 2. Pearson correlation between IPAQ scores and EMG features Total activity Vigorous activity Moderate activity Walking activity
RMS MNF −0.201 −0.032 −0.518 0.300 −0.512 0.126 −0.442 −0.097
MDF 0.066 0.424 0.223 0.048
In observing the muscle activation patterns with physical activity level among participants, regression line was plotted to fit the scattered data for both parameters. Results indicate that the time domain feature showed decreasing pattern as the IPAQ scores increasing. However, increasing pattern can be observed for frequency domain features. Regression value, R2 was not consistent and low for all features where the highest value was only 0.428 for RMS feature (Fig. 2).
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Fig. 2. Regression line fitted on IPAQ and RMS scattered data
4 Discussion This study aimed to evaluate the relationship between self-reported physical activity questionnaires with the muscle activation measured from surface electromyography analysis. Based on the previous study which evaluate the correlation between IPAQ data and other measures, various correlation values can be observed. Some research reported that IPAQ might be associated with overestimated of physical activity for some population when compared with accelerometer [3, 5]. Plus, a study conducted by Wanner et al. showed moderate correlation between those two objective and subjective measures [7]. Meanwhile, another study which compared the IPAQ data with other measures such as activity monitor able to show strong relationship for only total PA and vigorous physical activity [8]. This indicates that the correlation result was not limited to certain and same intensity level of physical activity. Therefore, our current study would be focusing on the relationship between IPAQ scores with another type of measures which is EMG data as individual physical activity might also influence human muscle activation. Our findings indicate that the correlation value varies for different EMG features with regards to different intensity of PA. Consistent coefficient value can only be observed for root mean square values where it has moderate to high correlation for all sub-intensity level, but not for total physical activity. Meanwhile, the lowest correlation was observed in all EMG features for total physical activity. This is in line with other studies where only certain intensity or domain can showed good relationship with the IPAQ scores. Apart from that, IPAQ are associated with the individual’s ability to recall their daily physical activity, whereby for the evaluation between different intensity levels; walking, moderate and vigorous activity, our present study showed that walking has the lowest correlation value for all EMG parameters compared to moderate
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and vigorous activity. This is in agreement with previous studies where moderate to vigorous activity are much more memorable, thus can be accurately recalled [13]. As for the scores obtained by the sub-domain, subjects tend to have the lowest level of physical activity at work domain. This can be interpreted as due to most of the participants in the present study are from university students, they might not really involved in job-related domain. These young adults are mostly tend to spend their time on leisure and sports activities. This showed why leisure activity domain had the highest percentage of mean physical activity scores for each domain. Our study are contradict with study conducted by Sebastiao et al. where the highest level in their study was reported for work and household domain. This was maybe due to the influence of different group of subjects that had been recruited, where they are mostly active adults with an average age of 44.8 years for men and 46.7 years old for women [3]. Besides that, leisure time had the highest score might be due to the participants’ regular exercise pattern, similar to a study reported by Chu et al. [6]. From the evaluation of the influence of physical activity on muscle activation pattern, it can be observed that the time domain features which is root mean square showed decreasing trend of muscle activation as the physical activity increases. It could be interpreted as individual with higher physical activity had lower RMS value. As mentioned by Ratnovsky et al., the increase of RMS value might be associated with the development of muscle fatigue [14]. Meanwhile, only a small increase of pattern can be observed for frequency domain features. Previous studies also showed that trained group has higher average of mean power frequency compared to untrained group [14]. Even though it showed that there was some trends between the physical activity and muscle activation, however, the regression R-squared value was quite low which indicate that in the current study, it is not enough to access the relationship of physical activity towards muscle activation pattern.
5 Conclusion This study able to investigate how individual physical activity influence the human muscle activation pattern. Several EMG features were being correlated with IPAQ scores. Overall, root mean square feature was the feature which had the best relationship with IPAQ MET-min/week scores based on the correlation analysis. The limitations of the current study was regarding the limitation of subject’s recruitment where only a small number of male university students were selected and being analysed. Thus, further studies should include varieties of subjects group with bigger number of subjects so that more reliable results can be obtained and used for general population.
References 1. Caspersen, C.J., Powell, K.E., Christenson, G.M.: Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public Health Rep. 100(2), 126–131 (1985). (Washington, D.C. 1974)
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Immediate Effect of Single Bout of Karate Exercise on Heart Rate Puneet Bhattacharya(&) and Sridip Chatterjee Department of Physical Education, Jadavpur University, Kolkata 700032, West Bengal, India [email protected], [email protected]
Abstract. Background: Physical activity of moderate intensity when incorporated in the daily routine provides a holistic development of the body and improves the overall health status. Heart rate acts as a marker of cardiac modulation by the sympathetic and vagal components of the autonomic nervous system. The immediate changes in terms of rise and recovery of heart rate levels after performing a bout of karate exercise may indicate the status of cardiovascular fitness levels of a physically active individual. The purpose of this study was to observe the immediate effect of a schedule karate regimen as a moderate exercise intervention on heart rate. Method: To fulfill the purpose of the study fifteen physically active male adults pursuing the Bachelor of Physical Education course were considered as subjects of the study. Purposive sampling method was used for collection of data. They were provided a continuous karate training protocol of ten minutes bout and their heart rate was recorded in three time intervals: pre intervention for ten minutes, during exercise and post recovery up to ten minutes. Holter test was used for measuring continuous heart rate. Results and Findings: The mean resting heart rate was recorded as 55.73 ± 5.17 beats/min, which with single karate bout went up to 144.20 ± 9.16 beats/min and again recovered in the 10th minute to 69.33 ± 5.96 beats/min. Repeated measure of ANOVA indicated that there was a significant difference in resting, exercise and recovery heart rates. Conclusion: It can thus be interpreted that the karate training protocol shows significant change of heart rate among pre, during and post exercise period. Keywords: Physical activity
Cardiac modulation Cardiovascular fitness
1 Introduction It is evident that regular physical activity is associated with better health outcomes. (Pate 2019; Slutsky 2016) The American Heart Association, the Centers for Disease Control and Prevention and the American College of Sports Medicine, all recommended regular physical activity of moderate intensity for the promotion, prevention and complementary treatment of overall health. (Pearson 2002; Haskell 2007; Agarwal 2012). Heart Rate is one of the most useful physiological variables for assessing and prescribing exercise for the maintenance of general fitness. (Hall 2015; Khoury 2019). Regular aerobic exercise of moderate intensity can help to achieve cardiovascular fitness (Wisloff 2010). Heart rate (HR) behavior has been extensively studied under different exercise-related types © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 223–234, 2020. https://doi.org/10.1007/978-981-15-3270-2_25
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and conditions as it is easy to measure heart rate. HR is primarily controlled by direct activity of the autonomic nervous system (Robinson 1966; Almeida 2003). Stimulation by the sympathetic nervous system results in positive chronotropic effect (increase in heart rate): The Sino atrial (SA) node is the predominant pacemaker of the heart. It is located within the upper posterior wall of the right atrium, and is responsible for maintaining sinus rhythm of between 60 and 100 beats per minute. This rate is constantly being affected by innervations from both the sympathetic and parasympathetic nervous systems. Stimulation by the sympathetic system nerves results in an increase of heart rate, as occurs during the “fight-or-flight” response. Positive inotropic effect in the form of increased myocardial contractility represents the ability of the heart to produce force during contraction. Stimulation by the sympathetic nervous system also enhances the conductivity of the electrical signal. On the other hand effects on chronotropy, ionotropy and conductivity get negative with activation of the parasympathetic nervous system (Gordan 2015). Because it is easy to measure, heart rate (HR) behavior has been extensively studied under different exercise-related types and conditions. HR is primarily controlled by direct activity of the autonomic nervous system (ANS), through actions on its sympathetic and parasympathetic branches on the sinus node autorhythmicity, especially resting vagal activity (parasympathetic), which is progressively inhibited since the exercise was started (Ekblom 1968), and sympathetic when exercise intensity is further incremented (Fig. 1). Different mechanisms act to adjust HR at different moments of a physical exercise. This mechanism is clearly shown in Fig. 1 below (White 2014).
Fig. 1. Heart rate autonomic control at rest and exercise. Source: White 2014
There are studies which determine and record resting heart rate, exercise heart rate and recovery rate up to a certain time limit but none so far on martial art form, karate (Ammann 2019). The immediate changes in terms of rise and recovery of heart rate levels after performing a bout of karate exercise may indicate the status of cardiovascular fitness levels of a physically active individual. Karate exercise is a mode of moderate intensity aerobic physical activity. The modality involves several muscle groups, with complex movements of rapid accelerations and decelerations. The
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attacking and defensive short duration techniques are characterized by performance with maximum intensity, interrupted by small intervals and make the modality comparable to an intermittent exercise. Karate exercise can be referred to as an activity that conditions the body to process and deliver oxygen more quickly and efficiently by strengthening the heart, lungs, vascular and autonomic nervous system. Not much scientific report is available to support the hypothesis that karate exercise could be considered as a mode of moderate intensity aerobic physical activity. The present researcher is particularly motivated to take up this study to support the hypothesis with some scientific experiment. If research can determine that karate exercise be performed at a medium and high level intensity, heart rate which would train the cardiovascular system; this would be an innovative step in validating this new form of conditioning program. 1.1
Objective of the Study
The purpose of this study was to observe the immediate effect of a single bout of karate exercise on heart rate responses in three different time intervals: resting phase, exercise phase and recovery phase.
2 Materials and Methods 2.1
Study Location and Subjects
This study was conducted in the Exercise Physiology Laboratory in the Department of Physical Education, Jadavpur University, Kolkata, West Bengal, India. The instruments and technical support for data collection was provided by the “Ayush” Diagnostic center, Dhakuria, Kolkata, West Bengal, India. This study was conducted on the running students of Physical Education (B.P.Ed). Fifteen (N = 15) physically active, healthy male adults between 22 to 28 years of age were selected as subjects for the present study and the subjects were briefed in detail about the study. These students had a minimum 6 months karate training experience. Permission was taken from the appropriate authority of the University where the subjects were pursuing their course (B.P.Ed). An individual consent was taken from each subject before participation in the training schedule. Detailed training protocol was approved by a board of subject experts in the field of research, Department of Physical Education, Jadavpur University. 2.2
Variables Studied
The variables for the present study and the measures for the study criterion were as follows: Anthropometric variables included were height, weight and body mass index (BMI). The details of these variables are given in Table 1.
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Sl. no 1 2 3 4
Variables Age in years measured through the date of birth (birth certificate) Height in cms by reference scale on the wall Weight in kgs by weighing machine Basal Metabolic Index
Mean ± SD 23.87 ± 0.83 in years 168 ± 2.92 in cms 61.4 ± 3.74 in kgs 21.75 ± 0.95
The physiological variable tested was heart rate, its study criterion is given in Table 2. Table 2. Physiological variable and its study criterion Sl. no Variable Test unit 1 Heart Rate measured by Holter Test Beats/min
2.3
Study Design
In the present study single group pre, during and post design was adopted. Purposive sampling method was used for collection of data. The complete design of the study is given in Fig. 2.
Fig. 2. The trial profile of the study
2.4
Administration of Test
To minimize possible circadian influences, measurements were performed at the time between 14 and 16 h. The electrodes were placed one by one on the selected sites, which include Right Arm (RA), Left Arm (LA), Ventral (V), Right Leg and Left leg
Recovery heart rate/10 min Recovery heart rate/9 min Recovery heart rate/8 min Recovery heart rate/7 min
Recovery heart rate/6 min
Recovery heart rate/5 min
Recovery heart rate/4 min
Recovery heart rate/3 min
Recovery heart rate/2 min
Recovery heart rate/1 min
Supine Rest for 10 min
Immediately after ten minutes of exercise
Recovery Heart Rate/10 min measurement Recovery Heart Rate/9 min measurement Recovery Heart Rate/8 min measurement
Recovery Heart Rate/7 min measurement
Recovery Heart Rate/6 min measurement
Recovery Heart Rate/5 min measurement
Recovery Heart Rate/4 min measurement
Recovery Heart Rate/3 min measurement
Recovery Heart Rate/2 min measurement
Recovery Heart Rate/1 min measurement
Resting Exercise Heart Rate Heart Rate Measurement Measurement
Table 3. Experimental sessions of recording the heart rate
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(LL) of each subject such that the heart rate could systematically be recorded in the Holter machine. The complete detail of the experimental sessions of recording the data have been shown in Table 3. The subjects were made to lie in the supine position and take rest for ten minutes. After the resting phase of stipulated ten minutes, the subjects were made to perform the training protocol shown in Table 4, continuously for a period of ten minutes. The testing exercise protocol was divided into four parts warming up exercises, Kihon or basics of karate which include attacks in the form of punches and kicks and defense in the form of blocks. Then after which they again lay down in the supine position and took rest for ten minutes in order to record the recovery heart rate. After the competition of the stipulated time the electrodes are slowly removed. The collected data was downloaded and analyzed using ARYTELL – D and 3 – CHANNEL respectively. Table 4. The exercise protocol Name of exercise
Type of exercise
Warming up Exercise
Head to toe rotation Jumping exercises Static and dynamic stretching Specific exercises: Jumping Jack, Burpees, Sit ups, Push Ups Kihon Punches (Both SonobaKihon * Jodan Tsuki (Face level punch) and IdoKihon) *Chudan Tsuki (Chest level punch) *Gedan Tsuki (Lower level punch) Blocks *Age Uke (Upper block) *Shoto Uke (Outer middle block) *Gedan Uke (Lower level block) Kicks *Mae Geri (Front kick) Kata Kihon Kata (Performed twice once half power and speed with counts, repeated in full power and speed without counts - Hajime) Cool Down Light stretching with deep inhalation and light exhalation and Seiza (meditative closing)
Duration 3 min
4 min
2 min
1 min Total Duration: 10 min
Source: 10kyu and 9thkyu grading syllabus for beginners recommended by the Japan Karate Association, H Q in Tokyo, Japan. https://www.jka.or.jp/wp/wpcontent/uploads/2017/06/b98c5e1514acc9fe91bbbc4b2fcb79 f2.pdf.
2.5
Statistical Analysis
Mean and standard deviation were used as descriptive statistics. In the present study the repeated measures of analysis of variance (RM ANOVA) was used for data analysis (Zar 1999). Repeated measures of ANOVA are an extension of t-tests. Here RM ANOVA was used to find out the significant difference between the three different time periods i.e. before exercise (resting phase), during exercise (exercise phase) and after exercise (recovery phase). Further Post Hoc Comparisons were done accordingly.
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3 Result A pre (resting phase), during (exercise phase) and post (recovery phase) single group design was followed for the present study. Single bout of karate exercise produces a significant change compared to its resting and recovery phase values. Descriptive data in the form of mean and ± SD are given in Table 5 followed by the graphical representation of resting heart rate, exercise and recovery heart rate (beats/min) in Fig. 3. Table 5. Descriptive Statics of the study group Sl. no Variable - Heart rate (beats/min) Mean 1 Resting Heart Rate (RHR) 55.73 2 Exercise Heart Rate (EHR) 144.20 3 Recovery Heart Rate 1 (RHR 1) 84.86 4 Recovery Heart Rate 2 (RHR 2) 77.33 5 Recovery Heart Rate 3 (RHR 3) 76.13 6 Recovery Heart Rate 4 (RHR 4) 74.73 7 Recovery Heart Rate 5 (RHR 5) 74.00 8 Recovery Heart Rate 6 (RHR 6) 73.13 9 Recovery Heart Rate 7 (RHR 7) 71.80 10 Recovery Heart Rate 8 (RHR 8) 71.06 11 Recovery Heart Rate 9 (RHR 8) 70.26 12 Recovery Heart Rate 10 (RHR10) 69.33
Standard deviation N 5.17 15 9.16 15 9.11 15 7.33 15 7.24 15 6.98 15 6.92 15 6.88 15 6.25 15 6.26 15 6.06 15 5.96 15
Graphical Representation of Heart Rate 160 140 120 100 80 60 40 20 0
144.2
84.86 55.73
77.33
76.13
74.73
74
73.13
71.8
71.06
70.26
69.33
Fig. 3. Line Graph based on mean values of Resting, Exercise and Recovery Heart Rate.
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Analysis of repeated measures (RM ANOVA) results are given in Table 6. Post Hoc analysis results are given respectively in Tables 7 and 8. Table 6. Repeated ANOVA within pre, during and post exercise sessions of heart rate Sl. no Source of variation 1 Total 2 Between Subjects 3 Within Subjects 4 Treatment 5 Residual or Interaction *. Significant at the 0.05 level F.05 = (11, 154) = 1.87
SS 86294.55 6072.80 80221.75 77962.15 2259.60
df MS F ratio 179 483.037 14 433.771 165 486.192 11 7087.468 154 14.673
Table 7. Pairwise comparisons of resting heart rate with other (exercise and recovery) experimental periods Pairwise comparisons Measure: Recovery heart rate I (Time) J (Time)
Mean Difference (I−J)
Std. Error
Sig.b 95% confidence interval for difference Lower Upper bound bound .000 −94.742 −82.191 .000 −33.864 −24.401 .000 −25.837 −17.363 .000 −24.632 −16.168 .000 −23.064 −14.936 .000 −22.344 −14.189 .000 −21.281 −13.519 .000 −19.646 −12.487 .000 −18.821 −11.846 .000 −17.978 −11.089 .000 −17.126 −10.074
Exercise HR −88.467* 2.926 Recovery HR 1 −29.133* 2.206 Recovery HR 2 −21.600* 1.976 Recovery HR 3 −20.400* 1.973 Recovery HR 4 −19.000* 1.895 Recovery HR 5 −18.267* 1.901 Recovery HR 6 −17.400* 1.809 Recovery HR 7 −16.067* 1.669 Recovery HR 8 −15.333* 1.626 Recovery HR 9 −14.533* 1.606 Recovery HR 10 −13.600* 1.644 • Based on estimated marginal means. • *. The mean difference is significant at the 0.05 level. • b. adjustment for multiple comparisons: Least significant difference (equivalent to no. of adjustments) Resting heart rate
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Table 8. Pairwise comparisons of exercise heart rate with other (resting and recovery) experimental periods Pairwise comparisons Measure: Recovery heart rate I (Time) J (Time)
Exercise heart rate
Mean difference (I−J)
Std. error
Sig.b 95% confidence interval for differenceb Lower Upper bound bound .000 82.191 94.742 .000 52.361 66.306 .000 61.029 72.704 .000 62.219 73.914 .000 63.816 75.118 .000 64.391 76.009 .000 65.257 76.877 .000 66.676 78.124 .000 67.463 78.804 .000 68.323 79.544 .000 69.389 80.344
Resting HR 88.467* 2.926 Recovery HR 1 59.333* 3.251 Recovery HR 2 66.867* 2.722 Recovery HR 3 68.067* 2.726 Recovery HR 4 69.467* 2.635 Recovery HR 5 70.200* 2.708 Recovery HR 6 71.067* 2.709 Recovery HR 7 72.400* 2.669 Recovery HR 8 73.133* 2.644 Recovery HR 9 73.933* 2.616 Recovery HR 10 74.867* 2.554 • Based on estimated marginal means. • *. The mean difference is significant at the 0.05 level. • b. adjustment for multiple comparisons: Least significant difference (equivalent to no. of adjustments)
Data in Table 6 reveals that significant difference was observed within the groups i.e. before exercise (resting phase), during exercise (exercise phase) and after exercise (recovery phase) for a period of ten minutes and that the calculated F-value was 483.037 whereas tabulated F-value was 1.87. It further interpreted that there was a significant difference that exists and Post-hoc comparisons need to be done. Pairwise comparisons are presented in Tables 7 and 8. It clearly shows that a significant difference was observed among resting heart rate, exercise heart rate and recovery heart rates of 1–10 min time period.
4 Discussion In the present study karate exercise was used as a moderate exercise intervention to observe the heart rate response in a group of young adults with a minimum six months karate training experience. The results of the present study show a significant change in the heart rate at the pre, during and post exercise period. The heart rate was measured using the Holter machine and descriptive statistics (mean ± SD) showed the Mean Resting Heart Rate as 55.73 ± 5.17 beats/min, which with single karate bout went up to 144.20 ± 9.16 beat/minute and again recovered in the 10th minute to 69.33 ± 5.96 beats/min. Repeated measure of ANOVA indicated that there was a significant difference in recovery heart rates from 1 to 10 min.
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Imamura et al. (1999), reported that heart rate increases with exercise and karate training have shown rise in maximal heart rate above the threshold values. However it can be revealed from previous studies were conducted on Taekwondo training and its effect on heart rate which showed that it was suitable for cardiovascular conditioning (Bridge 2007). In another study by Suetake 2017, on cardiac modulation and martial arts which included Judo, Muay Thai and Controls showed that Judo training after a nine months intervention showed greater dispersion of RR intervals, beat to beat when compared to baseline. Cross Sectional Studies like those by Bu 2010 and Imamura 1999 showed that martial art and karate training could affect heart rate and health status of the individuals, however they did not provide any affirmations to confirm karate as a moderate intensity exercise intervention, although some mention of health benefits of martial arts was corroborated by Bu 2010. The main intention of the present study was to observe the changes in heart rate and to see if they were significant, to characterize karate as an alternative activity for promotion of cardiovascular fitness. The changes that take place in heart rate at rest and at exercise are consequence of intrinsic adaptations of the sinus node, or derived from other physiological changes, such as the increased venous return, systolic volume, improved myocardial contractility, and enhanced oxygen use (Hall 2015). There are studies which also significantly show that aerobically fit individuals present a more effective autonomic activity than sedentary ones, and there is an indication that such individuals have better cardiac vagal tone. (Tulppo 1998). There are several studies on the relationship of autonomic nervous system and heart rate during exercise (Markovic 2008), but the type of exercise intervention being karate has minimal research. There are very few studies related to the present study, the studies are mostly on kumite (sparring) or on simulated sparring matches and heart rate response. (Invernizzi 2008; Güler 2018) Therefore the present study differs from the previous ones and is more novel. It can affirm karate as an intermittent modality of moderate aerobic intensity (Slimani 2018).
5 Conclusion Findings from the present study lead to an interpretation that the karate training protocol shows significant change in heart rate among pre, during and post exercise periods. Therefore we can conclude that such type of exercises can be used to maintain general cardiovascular health and fitness status. Moreover, this is probably the first study of its kind which provides scientific data and establishes the significance of karate as a moderate exercise intervention.
6 Recommendations In the light of the present study the following recommendations have been established:
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(a) Karate has been explored through the present study as an exercise which helps in the development of the overall health and fitness levels in individuals. (b) From the findings of the present study it said that karate which is widely known as a means of self-defense, can be utilized as an exercise intervention of moderate intensity to achieve an improved health status. (c) Comparative studies can be conducted between karate with other moderately aerobic exercises. (d) The role of heart rate and autonomic nervous system with karate as an exercise intervention can be further studied. (e) Therapeutic aspects of this modality as an exercise medicine can be studied.
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Incorporating Traditional Games in Physical Education Lesson to Increase Physical Activity Among Secondary School Students: A Preliminary Study ‘Arif Azlan1, Nadzirah Ismail1, Nor Farah Mohamad Fauzi2(&), and Ruzita Abd Talib1 1
Nutritional Science Program and Centre for Community Health, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia 2 Occupational Therapy Program and Centre for Community Health, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia [email protected]
Abstract. Physical education (PE) lesson is an important avenue for delivering physical activity (PA) opportunities during school hours. Non-sport activities like traditional games can be a practical way to promote PA during PE lesson, especially among those who are less inclined in sports. This study aims to determine whether playing traditional games during PE lesson can lead to greater PA compared to a ‘free-play’ PE lesson among secondary school students. A total of 56 subjects (Form 1: n = 27; Form 2: n = 29; mean age: 13.4 ± 0.5 years; mean BMI: 21.8 ± 4.9 kg/m2) from a school in Keramat, Kuala Lumpur were consented by their parents to participate in this study. PA was measured by using accelerometry (Actigraph GT3X+), on two separate PE lesson periods: PE lesson incorporated with traditional games and ‘free-play’ PE lesson. Subjects wore accelerometers for a total of 40 min during each PE lesson to determine total activity counts and moderate-to-vigorous physical activity (MVPA). The chosen traditional games were Galah Panjang and Baling Selipar. Mean total activity counts (p = 0.007) and time spent in MVPA (p = 0.006) were 20% and 19% greater respectively, during traditional games-based PE lesson compared to ‘free-play’ PE lesson. Time spent in sedentary activity was 45% lower during traditional games-based PE lesson (5.3 ± 4.3 min) compared ‘freeplay’ PE lesson (10.7 ± 11.7 min; p = 0.006). Boys appeared to be 25% more active than girls in this study. In conclusion, incorporating fun and meaningful activities like traditional games during PE lessons can serve as an alternative strategy to promote PA during school hours. Further studies are warranted to determine other types of traditional games that may promote PA in girls. Keywords: MVPA
Adolescents Accelerometer Sports Sedentary
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1 Introduction Physical activity (PA) is an essential contributing factor to children’s and adolescents’ well-being [1]. According to the Active Healthy Kids Global Alliance report from 49 countries however, children around the world were not getting enough PA, consequent to urbanisation and technological advancement [2]. The Malaysian School-Based Nutrition Survey (MSNS) reported that 50% of Malaysian school children aged 10 to 17 years were physically inactive, with girls being less active compared to boys [3]. The PA recommendations for children and adolescents is 60 min of moderate-tovigorous physical activity (MVPA) [4]. The lack of activity has major implications for the health of children, and may be responsible for the rising paediatric obesity pandemic. Reducing physical inactivity would certainly reduce the risk of noncommunicable diseases during childhood, as well as when they reach adulthood [5]. School physical education (PE) provides an excellent avenue for children and adolescents to be physical active during school hours [6]. A high-quality PE curriculum enables all students to enjoy the different types of PA, apart from conferring many positive benefits to physical and mental health such as improving cardiorespiratory fitness and body composition [7], increased cognitive and academic performance [8, 9] as well as reducing mental stress among school children [10]. A study by Chen et al. [11] indicated that school children who had greater frequency of participation in PE lessons were more likely to spend greater time in MVPA, even after school hours. Silva et al. [12] suggested that an average of two times per week of PE lessons is needed to achieve an overall improvement on weekly PA both in and out of school. PE is a compulsory subject taught in Malaysian primary and secondary schools and is divided into two parts; physical education (taught outside classroom) and health education (assigned topics taught in classroom) [13]. However, PE has become a less-favored subject in the recent years and often viewed as s marginal subject within the curriculum, especially among secondary school students [14, 15]. Apart from a well-designed PE curriculum, the effectiveness of PE lesson delivery relies heavily on the teacher’s competency and enthusiasm to motivate students to participate in PA [16]. It is not uncommon to find non-specialised teachers teaching PE in schools and this contributes significantly to the delivery of quality PE [17]. Tan and Lee [18] had previously reported a high incidence of lack of observation and supervision of PE lessons by school administrators in Malaysian schools, leading to inconsistencies as to how PE lessons are conducted across many schools [13]. Apart from the personnel factor, other studies reported that lack of sporting equipment and facilities and conducive space were among the factors impeding students’ participation in PE lesson [19–21]. Perhaps the most sustainable and quickest approach to promote PA during PE lessons among school children is to incorporate fun and meaningful activities [22], that will appeal to not only sports-inclined students, but also to those who deemed themselves as ‘less sporty’ [23]. Such example is playing traditional games. Traditional games are simple in design and implementation, suitable in all weather conditions with low-cost, space, time and equipment, but still capable of promoting PA, comparable to playing organised sports [24]. Traditional games are not constrained by strict rules and regulations, therefore these games are often regarded as play and leisure activities,
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hence performed for the sole purpose of enjoyment [25]. The enjoyment factor in traditional games can be an excellent way to motivate students who are less physically active to be active during PE lessons, something which organised sports cannot do [26]. Furthermore, traditional games played on a regular basis in schools have been shown to increase students’ physical self-efficacy; a term used to refer to a student’s feeling of inclusion and engagement in PA [27]. Malaysia is a country rich with cultural heritage, especially on traditional games. Among the various types of traditional games played in Malaysia are Gasing, Batu Seremban, Teng-Teng, Polis Sentri, Baling Selipar, Galah Panjang and Konda Kondi [28]. Traditional games were formerly popular and played by a wide range of age and race, however, its popularity has dwindled over the last few decades and is less practiced by the younger generations these days [29]. The UNESCO encourages promotion of traditional games in order to foster cultural identities and respect for communities from different cultural background [30, 31]. Re-introducing traditional games into PE lessons would not only promote the younger generation to appreciate Malaysian heritage and culture, but also an alternative strategy to promote PA and health-related fitness among school children [30]. A recent intervention study in Iran demonstrated a positive effect of PE and traditional games on reducing overweight problem among secondary school girls [32]. Other studies have reported that playing traditional games improved motor-related fitness like agility, speed and balance among primary and secondary school students [33, 34]. However, the levels of PA engaged while playing games were not thoroughly assessed in these studies. Furthermore, it is not currently known whether playing traditional games during PE lesson would lead to a comparable PA level to that of PE lessons taught in schools. Therefore, the aim of this study was to determine and compare PA variables between playing traditional games and ‘free-play’ during PE lessons among secondary school students. Further attention will be focused on differences of PA levels between gender and across BMI categories.
2 Methodology 2.1
Study Design and Sampling
This was a cross-sectional study designed to compare PA between traditional gamebased PE lesson (TG-PE) and ‘free-play’ PE lesson among students of a secondary school in Keramat, Kuala Lumpur. Subjects for this study were recruited from Form 1 (n = 1) and Form 2 (n = 1) classes, aged between 13–14 years old via purposive sampling. Subjects were excluded if they reported having chronic medical conditions and physical disabilities that would limit movement. A total of 56 subjects were involved in this study. 2.2
Anthropometric Measurement
Subjects underwent anthropometric measurement prior to the start of the study. Height and weight were measured using a portable stadiometer (SECA, German) and digital weighing scale respectively (SECA, German). Body mass index (BMI) was calculated
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and categorised according to BMI-for-age z score [35]. Waist circumference was measured using Lufkin tape W606PM (Lufkin, USA), while Omron Body Fat Analyser HBF320 (Omron, Japan) was used to measure subjects’ body fat percentage. Waist circumference measurement was used to classify abdominal obesity based on Poh et al. [36]. 2.3
Study Protocol
The study was conducted during two, individual PE lessons across two weeks. In the first week, subjects followed a 40-min ‘free-play’ PE period, defined as an unstructured lesson during which students had the freedom to carry out their preferred PA, monitored by the PE teacher. In the second week, subjects followed a 40-min PE lesson incorporated with traditional games. Two traditional games were selected for this study; i.e. Galah Panjang and Baling Selipar. The Galah Panjang is a game that involves two teams, in which one team is required to run pass several parallel lines, guarded by the opposing team, without being touched or tagged by the opposing team [34, 37]. The Baling Selipar game also involves two teams; the ‘attack’ and ‘defend’ teams. It is a strategic game, revolving around the mechanism of ‘build-destroy-rebuild a pyramid’. The defending team is required to build a pyramid on the ground, using three rubber slippers, leaning against each other. The attacking team is tasked to destroy the pyramid by knocking down the pyramid arrangement using a slipper, or eliminating their opponents by striking them with the same slipper [30, 37]. Each game was played for 20 min in multiple groups. PA was measured during both PE lessons using accelerometry devices. 2.4
Physical Activity Measurement
PA was measured using Actigraph GT3X+ (Pensacola, Florida, USA). Subjects were instructed to wear the accelerometer attached to an elasticised belt around the waist, positioned just above the right hip during the PE lessons. The data was downloaded using Actilife software version 6.13.2. The level of physical activity were evaluated as total activity counts, time spent in moderate-vigorous PA (MVPA) determined based on Freedson cut-off point [38], time spent in sedentary activity and steps count. 2.5
Ethical Issues
Approval to conduct the study was obtained from the Universiti Kebangsaan Malaysia Research Ethics Committee (UKM1.21.3/244/NN-2018-130) and the Ministry of Education (KPM.600-3/2/3-eras(1151)). Parental informed consent for each subject was obtained prior to data collection. 2.6
Statistical Analysis
Data was analysed using Statistical Package for Social Science (SPSS) version 23. Shapiro-Wilk test was used to test the normality of data. Descriptive analysis (frequencies, percentages, means ± standard deviations) was used to report demographic,
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anthropometric and PA data. Paired t-test was used to compare PA variables during ‘free-play’ PE and traditional games-based PE lessons. Independent t-test was used to test the difference of PA between gender. The difference of PA among BMI categories was tested using one-way ANOVA.
3 Result 3.1
Demographic Data
A total of 56 subjects from Form 1 (n = 27) and Form 2 (n = 29) were involved in this study. Subjects’ mean age was 13 ± 1 years. The majority of the subjects were boys (57.1%; n = 32) and Malays (96.4%; n = 54). 3.2
Anthropometric Data
Table 1 showed anthropometric data of subjects. Subjects’ weight, waist circumference and body fat percentage were 53.9 ± 16.4 kg, 68.1 ± 13.1 cm and 25.0 ± 6.6%, respectively. According to BMI-for-age categories, 52% of subjects were categorised as normal, 21% were overweight, and 27% were obese. There were more obese boys (34%) compared to obese girls (17%). Overall, only 8% of the subjects fell under the abdominal obesity category. Table 1. Subjects’ anthropometric data (n = 56) Characteristics Weight (kg) Height (cm) Waist circumference (cm) BMI (kg/m2) Body fat (%) BMI categories Normal ( 2 SD) Overweight (2–3 SD) Obese (>3 SD) Waist circumference categories No risk abdominal obesity (90%)
3.3
Overall (n = 56) Boys (n = 32) 53.9 ± 16.4 57.7 ± 18.8 155.9 ± 8.9 159.4 ± 9.3 68.1 ± 13.1 72.3 ± 13.9 21.8 ± 4.9 22.2 ± 5.3 25.0 ± 6.6 23.2 ± 6.2
Girls (n = 24) 48.9 ± 11.1 151.1 ± 5.5 62.6 ± 9.95 21.3 ± 4.4 27.4 ± 6.4
52% 21% 27%
44% 22% 34%
62% 21% 17%
92% 8%
78% 22%
92% 8%
Physical Activity Data
Table 2 showed comparison of PA variables between traditional games-based PE lesson (TG-PE) and ‘free-play’ PE lesson. Total activity counts showed a significant, 20% increase during TG-PE lesson (113832 ± 32075) compared to ‘free-play’ PE lesson (90662 ± 55042; p = 0.007). Time spent in moderate-to-vigorous PA (MVPA)
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during TG-PE lesson (28.9 ± 6.3 min) was 19% higher than that in ‘free-play’ PE lesson (23.5 ± 12.8 min; p = 0.006). Time spent in sedentary activity was reduced as much as 45% during TG-PE lesson (5.3 ± 4.3 min) compared to ‘free-play’ PE lesson (10.7 ± 11.7 min; p = 0.006). Table 2. Comparison of physical activity variables between ‘Free-Play’ PE lesson and traditional games-based PE lesson (TG-PE) PA variables ‘Free-Play’ PE lesson TG-PE lesson Total activity counts 90662 ± 55042 113832 ± 32075 Time spent in MVPA (minutes) 23.5 ± 12.8 28.9 ± 6.3 Time spent in sedentary (minutes) 10.7 ± 11.7 5.3 ± 4.3 Step count 1066 ± 890 1379 ± 455
3.4
P value 0.007 0.006 0.003 0.010
Comparison of Physical Activity Between Gender
Table 3 showed the gender comparison for PA variables between traditional gamesbased PE lesson (TG-PE) and ‘free-play’ PE lesson. Boys recorded a significantly higher step count (1287 ± 1023 steps) compared to girls (772 ± 570 steps; p = 0.031) during the ‘free-play’ PE lesson. However, there were no significant differences for time spent in sedentary, time spent in MVPA and total activity counts between boys and girls during the same lesson. On the other hand, total activity counts (boys: 126585 ± 30966; girls: 96829 ± 25293; p = 0.000), time spent in MVPA (boys: 30.9 ± 5.6 min; girls: 26.2 ± 6.2 min; p = 0.000) and step count (boys: 1563 ± 472 steps; girls: 1134 ± 290 steps; p = 0.000) were significantly greater in boys compared to girls during TG-PE lesson. Within the boys group, total activity counts (21%; p = 0.018) and time spent in MVPA (19%; p = 0.012) showed significant increases, while time spent in sedentary decreased significantly (−48%; p = 0.021) during TG-PE lesson compared to ‘freeplay’ PE lesson. Within the girls group, time spent in sedentary decreased significantly (−52%; p = 0.041) while steps count showed significantly increases (32%; p = 0.006) during TG-PE lesson compared to ‘free-play’ PE lesson. 3.5
Comparison of Physical Activity Across BMI Categories
Table 4 showed comparison of PA variables between traditional games-based PE lesson (TG-PE) and ‘free-play’ PE lesson across BMI categories. There were no significant differences in PA variables across BMI categories in both TG-PE lesson and ‘free-play’ PE lesson. PA also did not differ between TG-PE lesson and ‘free-play’ PE lesson within each BMI category.
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Table 3. Gender comparison for physical activity variables between ‘Free-Play’ PE lesson and traditional games-based PE lesson (TG-PE) PA variables ‘Free-Play’ PE lesson TG-PE lesson Total activity counts Boys (n = 32) 99666 ± 54587 126585 ± 30966a,b Girls (n = 24) 78657 ± 54456 96829 ± 25293 Time spent in MVPA (minutes) Boys (n = 32) 25.0 ± 11.5 30.9 ± 5.6a,b Girls (n = 24) 21.5 ± 14.2 26.2 ± 6.2 Time spent in sedentary (minutes) Boys (n = 32) 8.4 ± 9.1 4.4 ± 3.7b Girls (n = 24) 13.7 ± 14.1 6.6 ± 4.8b Step count Boys (n = 32) 1287 ± 1023a 1563 ± 472a Girls (n = 24) 772 ± 570 1134 ± 290a,b a significant comparison between gender within the same PE lesson b significant comparison between PE lessons within the same gender Table 4. Comparison of physical activity variables between ‘Free-Play’ PE lesson and traditional games-based PE lesson across BMI Categories PA variables ‘Free-Play’ PE lesson Total activity counts Normal (n = 23) 88892 ± 57454 Overweight (n = 12) 86963 ± 57300 Obese (n = 15) 97043 ± 51563 Time spent in MVPA (minutes) Normal (n = 23) 22.9 ± 13.8 Overweight (n = 12) 22.6 ± 13.5 Obese (n = 15) 25.3 ± 10.4 Time spent in sedentary (minutes) Normal (n = 23) 12.3 ± 12.5 Overweight (n = 12) 11.4 ± 11.6 Obese (n = 15) 6.9 ± 11.7 Step count Normal (n = 23) 1007 ± 785 Overweight (n = 12) 1053 ± 998 Obese (n = 15) 1191 ± 1037
TG-PE lesson 114443 ± 29784 109190 ± 29909 116367 ± 39224 28.5 ± 5.1 29.3 ± 6.5 29.3 ± 8.4 5.1 ± 3.1 5.0 ± 4.2 6.0 ± 6.2 1406 ± 424 1392 ± 516 1318 ± 487
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4 Discussion To our knowledge, this is the first study to be documented in Malaysia which measured PA levels while playing traditional games using accelerometry among secondary school children. The primary aim of this study was to compare PA levels during PE lesson incorporated with traditional games and a ‘free-play’ PE lesson. We hypothesised that playing traditional games during PE would result in a greater PA levels compare to a ‘free-play’ PE lesson. Overall, our study demonstrated that playing traditional games was more effective at increasing overall PA, as well as reducing time spent in sedentary activity, compared to a ‘free-play’ PE lesson. In this study, ‘freeplay’ PE lesson is defined as a lesson without a structured activity plan. While the standard national PE curriculum covered structured lessons like athletics, games and gymnastics, it is a prevalent practice that these structured lessons are sometimes substituted with a ‘free play’ period. One the reasons being PE teachers having no or little training in conducting the aforementioned structured activities [13]. Unfortunately, a ‘free-play’ period does not necessarily translate into student participation in physical activity, and this was proven by our current finding that the time spent in sedentary activity was nearly 50% more in the ‘free-play’ PE compared to traditional gamesbased PE lesson. Our findings also demonstrated that playing traditional games not only increased PA in general, but also time spent in MVPA. In the current educational systems, students spend up to 97% of their time in school sitting in a traditional classroom setting [39], therefore PE is considered a predominant method to promote MVPA and reduce sedentariness during school hours [40]. It is recommended that students engage in MVPA for at least 50% of the time they spend in PE class, one of the most critical outcome measures in determining the quality of a PE program [41], consistent with the evidence pointing to the association of MVPA with physical fitness and mental health [42]. The mean time spent in MVPA in the traditional games-based PE lesson was 56% of the lesson time, indicating that traditional games can be a strategy to achieve MVPA at least 50% of the lesson time criterion. Fairclough and Stratton [43] had demonstrated that team games promoted the highest levels of MVPA compared to individual activities and games. Team games like traditional games require less specific skills were more likely to be perceived as fun and exciting, which is a strong motivating factor for engagement in PA [44]. Lavega et al. [45] also justified that the purpose of playing traditional games is more on promoting enjoyment rather than competitiveness, and this may appeal to students who are less inclined in competitive sports or games [39]. Furthermore, Chen et al. [11] in his study demonstrated that increased MVPA during PE was associated with a corresponding increase in daily MVPA and reduced sedentary behaviour, highlighting the importance of PE in accumulating MVPA in youth’s daily lives. Increase in MVPA also means that opportunities to promote cardiorespiratory health may be more significant. As expected, this study observed that boys were generally 25% more active compared to girls, and boys also spent a greater proportion (18%) of lesson time involved in MVPA during the traditional games-based PE lesson compared to girls. This finding is consistent with many previous studies [46–48] that recognised gender
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differences with regards to PA participation. Boys are generally more concerned with sport and team-based activities, as well as possessing competitive streaks, while girls are more engaged in individual activities like dance, gymnastics, and swimming [43, 49]. It is also apparent that the nature of the traditional games employed in this study required short burst of high-intensity movements, thus it is likely that the girls were less motivated than the boys to physically exert themselves. According to Telford et al. [50], the gap of PA between gender could also be explained by girls being less favourably influenced by socio-ecological factors at the individual, family, school and environmental levels. While MVPA did not differ between traditional games-based PE lesson and ‘free-play’ PE lesson among girls in the study, the girls spent approximately 50% lesser time in sedentary activity, as well as recorded higher step count during traditional games-based PE lesson, suggesting that playing traditional games may provide a boost for PA among school girls. Bronikowska et al. [51] explained that girls do enjoy traditional games due to the activity requiring less specific skills, less competitiveness and allowing them to move at their own pace when playing. In contrast to gender comparison, the present study did not observe any differences in PA variables among normal, overweight and obese subjects. Many studies on the other hand, reported that PA levels were often lower in obese children compared to normal weight children [52–54]. The lack of difference could be explained by the type of activities that the subjects engaged in during PE lessons. While reports have shown that students with high BMI were associated with lower perceptions of physical competence than students with lower BMI [55, 56], playing traditional games as opposed to organised sports, require less complex skill set and may be perceived as less daunting by those who are ‘less physically-competent’. This finding indicates that traditional games can be an excellent option to encourage equal participation in PA among youth regardless of body sizes or BMI. Overall, our study shows that playing traditional games like Galah Panjang and Baling Selipar is an excellent option in lieu of unstructured PE lessons which are commonly practiced in schools these days. When students are at liberty of carrying out their own physical activity, this can lead to issues like spending little effort during PE lessons [57], or avoiding participation altogether [58], especially when supervision is minimal, thus contributing to the declining participation in PE lessons. The advantage of incorporating traditional games during PE lesson is that it requires minimal equipment and space than organised sports. As for the PE teachers, they do not need specific skills or training to conduct the games, making it especially convenient for nonspecialised PE teachers. This study has several limitations however. Although the types of traditional games (Galah Panjang and Baling Selipar) chosen for this study were effective at increasing PA during PE lesson, we did not manage to determine PA variables for each game separately, therefore we could not determine which one traditional game is more advantageous than the other with regards to promoting MVPA, if such difference exists. This certainly highlights the need for such studies in the future. Secondly, the sample size for this study was relatively small due to limitation of accelerometers availability, but we feel it is sufficient to provide the baseline information needed for planning future interventions involving traditional games in a bigger scale among school children. Lastly, we conclude our study findings with in a caveat in mind that
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the comparison of PA was made against an unstructured PE lesson or ‘free-play’ period, which by no means represent the national PE curriculum used by Malaysian schools. If similar studies were to be carried out to compare PA between traditionalgames based PE and structured PE lessons as laid out by the standard syllabus, a different outcome may emerge and this would warrant a further investigation.
5 Conclusion Substituting a ‘free-play’ PE lesson with playing traditional games is effective and increasing PA among secondary school students. Incorporating fun and enjoyable activities like traditional games during PE lessons is vital in promoting PA during school hours. Future studies should expand into examining other types of traditional games and to determine which types of games that are more attractive and appealing to school girls to boost PA in this particular gender group. Acknowledgments. We would like to acknowledge all the subjects who took part in the study, the school principal and teachers of the school involved. Conflict of Interest. The authors declare that there are no conflicts of interest regarding the publication of this paper.
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52. Kee, C., et al.: Physical activity and sedentary behaviour among adolescents in petaling district, selangor, malaysia. Malays. J. Med. Health Sci. 7(1), 83–93 (2011) 53. Olds, T.S., et al.: Obese adolescents are less active than their normal-weight peers, but wherein lies the difference? J. Adolesc. Health 48(2), 189–195 (2011) 54. Katzmarzyk, P.T., et al.: Physical activity, sedentary time, and obesity in an international sample of children. Med. Sci. Sports Exerc. 47(10), 2062–2069 (2015) 55. Carissimi, A., et al.: Physical self-efficacy is associated to body mass index in schoolchildren. Jornal de Pediatria 93(1), 64–69 (2017) 56. Craft, L.L., et al.: Predictors of physical competence in adolescent girls. J. Youth Adolesc. 32(6), 431–438 (2003) 57. Ntoumanis, N., et al.: An idiographic analysis of a motivation in compulsory school physical education. J. Sport Exerc. Psychol. 26(2), 197–214 (2004) 58. Brooks, F., Magnusson, J.: Taking part counts: adolescents’ experiences of the transition from inactivity to active participation in school-based physical education. Health Educ. Res. 21(6), 872–883 (2006)
Muscle Strength in Male Youth that Play Archery During Leisure Time Activity Norsham Juliana1(&) , Izuddin Fahmy Abu2 , Nadia Ahmad Roslan1, Nur Islami Mohd Fahmi Teng3 Abd Rahman Hayati1 , and Sahar Azmani1
,
1
Universiti Sains Islam Malaysia, 71800 Nilai, Negeri Sembilan, Malaysia [email protected] 2 Universiti Kuala Lumpur Institute of Medical Science Technology (UniKL MESTECH), 43000 Kajang, Selangor, Malaysia 3 Universiti Teknologi Mara (UiTM), 42300 Puncak Alam, Selangor, Malaysia
Abstract. Archery involves repetitive isometric contraction of muscles, however, there is a paucity in scientific evidence that describes the muscle strength in those receiving archery training. This study aimed to determine the differences in maximum force in selected groups of muscles between healthy youth with regular archery training and those without any background of resistance training. A case-control study design was adopted to compare between youth with archery training as subjects (n = 40) and youth without any background of resistance training as control (n = 78). Both groups were matched based on age, race, education level, income, time spent for weekly physical activities, and body composition. Muscle strength was assessed via JTech Commander PowerTrack MMT and the forces were recorded in Pound-force (lbf). Subjects with archery training showed significantly (p < 0.05) higher mean of muscle strength’s maximal force as compared to the control group in shoulder motions such as higher abduction strength (11%), adduction strength (15%), flexion and extension strength (19%). Elbow motion showed significantly higher extension strength by 17%. Similarly, higher lower body muscle strength was also found in subjects with archery training as compared to subjects in the control group in their hip motions for abduction (16%) and adduction (21%) and knee motion for extension (25%). Training in archery has a significant impact on muscle strength of both upper and lower body as shown in these youths. Therefore, serious attention should be given archery and be further promoted as a physical activity in the enhancement of health. Keywords: Muscle strength
Isometric exercise Archery
1 Introduction Muscle strength is imperative in maintaining physical function, mobility and vitality throughout life. There are negative linear relationships reported between muscle strength with risk of fall, morbidity, and mortality [1]. Muscle mass has always been one of the parameters believed to highly influence its strength. However, Goodpaster et al. [2] elucidated that the loss of strength does not depend exclusively on the mass © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 248–256, 2020. https://doi.org/10.1007/978-981-15-3270-2_27
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but rather a deterioration in muscle quality [2]. Regular exercise or involvement in sports are established factors that enhance the quality of muscles. Recent review on muscle strength focuses on multiple models that are able to improve muscles’ maximal force expression and time-limited force expression. The models recommend various types of training that include bilateral, eccentric and accentuated loading, and variable resistance training to be the activities that may greatly produce comprehensive strength adaptations. All the models are tailored to professional athletes and may not be adaptable by the general population due to its vigorous nature of training [3]. However, other less aggressive approaches with relatively similar effects on muscle strength should be promoted. Archery is often perceived as either an elite sport or stationary sport. The training in archery involves a consistent sequence of movements during execution of a single shot. Part of important skills to be adopted in archery training are stance positioning, bow and arrow preparation, drawing the bow string to the full draw, aiming and releasing the arrow [4]. Earlier studies reported the importance of combined muscular contraction-relaxation sequence in the training. There is a static equilibrium achieved in muscles contraction at the wrist and elbow of the arm before the release of arrow [5]. The sport is commercially advertised to have significant physical and mental health benefits. However, up to date scientific evidence on the health benefits are still scarce. A number of studies addressed the regression of young adults being engaged in physical activities in the recent decade. The unhealthy lifestyle promotes early onset of musculoskeletal disorders and physical inability. Hence, it is crucial to provide sufficient information on activities that are able to retain muscle function and enhance its strength [6, 7]. It is generally known that heavy resistance training increases skeletal muscle size and strength regardless of gender or age. Previous study revealed that male and female body builders have 54% to 147% greater muscle fibre cross-sectional area as compared to age matched controls [8]. However, considerably less is known about isometric training that do not involve heavy resistance particularly archery, in its attribution to muscle strength. Up to date, studies on archery focus more on the strategies to increase accuracy in hitting the target. Our study aimed to assess the differences in maximal force in selected group of muscles representing the upper and lower body in healthy youths receiving archery training and compared to those without any resistance training.
2 Methodology 2.1
Study Design
This is a case-control study conducted as part of the Physiological and Physical Fitness of Malaysian Male Youth Programme in Malaysia. The sampling frame includes healthy male aged 18 to 30 years old. Sample size calculation was done using the PS software, using the mean difference value of 10.9, sd 16.8 (Bianco et al. 2015) at a confidence interval of 95% and power of 80%. Minimum sample size based on 1:1 case to control ratio is 38 subjects for cases and controls. Those who had a history of musculoskeletal injuries, any communicable or non-communicable diseases, congenital
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disorders, drug abuse or growth disorders were excluded from this study. Also excluded were subjects involved in any isometric training besides archery such as weight lifting, resistance bands exercise and rock climbing as well as professional archers representing Malaysian athletes. Case were youths undergoing formal training in archery for at least one year. Their training regimen may vary depending on the centres but all subjects included were those with high compliance for training of at least twice every week for two hours. Controls on the other hand were those without any training or past experience in archery. Their age and body mass index (BMI) were matched with subjects in the archery group. Advertisement with specific inclusion and exclusion criteria was done using flyers and posters at all the identified venues. The recruitment was conducted from July 2016 until July 2017. The study protocol was reviewed and approved by the Ethics Committee of Universiti Sains Islam Malaysia (Ethical number: USIM/REC/0416-3). All archery players from archery clubs around Klang Valley aged between 18 and 30 years old were approached to participate in this study. Controls subjects were selected based on matched criteria with the selected subjects in the case group. All subjects were screened using a detailed demographic questionnaire. Their states of health were screened based on previous medical records, history and basic physical examination performed by physicians. They were briefed thoroughly on the study and a written informed consent was obtained from each one. Demographic data included are their age, education level and income. 2.2
Body Anthropometry
Subjects’ height (without shoes) were estimated using InBody BSM 170/170B Stadiometer (Korea). Their weight, fat free mass, fat mass, and fat percentage with light clothing without shoes was determined via In Body 270 Body Impedance Analyser (Korea). A BMI of >24.9 kg/m2 was categorised in overweight/obese group whilst a BMI of 18.5–24.9 kg/m2 was categorised in normal group. Subjects were also classified based on their adiposity. A high adiposity was defined as having 19% or more of body fat percentage. 2.3
Muscle Strength Assessment
Muscle strength were assessed via JTech Commander Power Track MMT and the force was recorded in Pound-force (lbf), measured to the nearest 0.1 lbf. The handheld dynamometer was used to measure the force generated by a group of muscles involved. Subjects were instructed to perform maximum isometric contraction during dynamometry measurements. The dynamometer was placed perpendicular to the tested limb. All tests were done in supine position except for knee flexion and extension, which were done in sitting position. Trained healthy examiner was involved in data collection as the resistance must be applied by the examiner to avoid movement of the limb that was tested. One-minute gaps were given between two consecutive trials for each group of muscles. The highest force produced during each session will be recorded. Test sequence starts with assessment of the upper body followed by lower body and similar procedures were adopted for all subjects [9, 10].
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Statistical Analyses
The data were analysed using the IBM Statistical Package for the Social Sciences version 24.0 software (USA). Independent t test was utilised to determine the difference of means in all quantitative data whilst chi squared (v2) test was used in the analyses of categorical data. The level of significance was set at p < 0.05.
3 Results A total of 40 archery players who fulfilled the strict inclusion and exclusion criteria were recruited in this study. Comparative data were collected from 73 youths, as controls with matching criteria as the study subjects. Both case and control group showed homogeneity in their demographic data with no significant difference (p > 0.05) based on the v2 test. They were also matched by their body compositions with no difference (p > 0.05) based on independent t test (Table 1). Table 1. Demographic and anthropometric parameters between case and control subjects. Parameters Case (Archery); n = 40 Control; n = 73 22.5 + 2.98* Age 19.4 + 4.28* 61 38 Race 11 1 Malay 1 1 Indian Chinese 19 35 Education level 21 35 Secondary Tertiary 20 34 Income 6 18 RM 5000 Body mass index 23.7 + 5.2* 23.5 + 5.0* Total body water 38.2 + 5.5* 37.6 + 5.5* Fat free mass 52.0 + 7.7* 51.3 + 7.5* Skeletal muscle mass 29.1 + 4.6* 28.8 + 4.5* Percentage of body fat 20.6 + 8.1* 21.3 + 9.1* NS: not significant (p > 0.05) * data is presented as mean + standard deviation. b independent t test; ± v2 test
p value 0.87b 0.11±
0.80±
0.47±
0.59b 0.68b 0.67b 0.63b 0.50b
Measurement of the upper body included assessment of maximal force executed by groups of muscles that are involved in shoulder, elbow and wrist general motion. The maximal force during hip and knee motion were measured to determine the strength of the lower body. Based on the result in Table 2, those with archery training have higher mean of maximal force in muscle strength for all parameters assessed as compared to
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those without the training. Significant differences (p < 0.05) recorded in the result of muscle force in shoulder motions (abduction, adduction, flexion, and extension), elbow motion (extension), hip motions (abduction and adduction), and knee motion (extension) suggested that the upper and lower body muscle strength of youth involved in archery training was higher as compared to the control group. Table 2. Upper body and lower body muscle strength between case and control. Upper body Case (Archery); n = 40 Control; n = 73 p value 32.7 + 7.7 29.4 + 9.1 0.047* Shoulder 0.014* Abduction* 31.2 + 8.2 27.1 + 8.6 0.009* Adduction* 38.1 + 11.6 32.1 + 11.2 0.011* Flexion* 40.2 + 13.0 33.7 + 12.1 0.069 Extension* 27.0 + 7.2 24.4 + 6.9 Rotation 36.0 + 12.2 Elbow 33.4 + 11.8 0.28 Flexion 30.5 + 10.0 26.0 + 9.1 0.021* Extension* 23.3 + 7.0 Wrist 21.7 + 6.9 0.221 Flexion 20.0 + 6.1 18.6 + 6.6 0.286 Extension Lower body Case (Archery); n = 40 Control; n = 73 p value 34.3 + 10.5 29.5 + 10.0 0.021* Hip 0.009* 25.2 + 10.0 Abduction* 30.4 + 9.5 0.210 31.1 + 10.3 Adduction* 33.5 + 9.4 0.093 Flexion 39.2 + 10.8 35.3 + 12.1 Extension Knee 27.5 + 10.0 24.8 + 8.9 0.149 Flexion 37.2 + 15.0 29.8 + 13.0 0.011* Extension * Data is presented as mean + standard deviation and the unit of force is lbf. * significant with p < 0.05 based on independent t test.
4 Discussion Body composition is part of the major determinant for muscle strength, therefore those who are thinner are found to have relatively poorer muscle strength compared to those who have higher body mass index. This study found that at any levels of body mass index (BMI), there is a wide variability in strength that correlate not with the BMI instead with the types of leisure time activity. Hence in this study highlights that regular training of archery brings positive impact in increasing muscle strength among male youths. Other types of physical activities that do not involve heavy resistance but greatly enhance muscle strength include swimming, squat jumps and tennis. Most of the studies showed that the superior effects are either on the strength of the upper body
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or the lower body, as a result of training [11, 12]. Interestingly, our study found that archery has impact on both the upper as well as lower body strength. Archery involves contraction and relaxation strategy of forearm muscles during the release of bowstring. The discipline to achieve accuracy involves three phases that include the stance, drawing and sighting. Each of the phases require stable sequence of movements, thus multiple muscles are recruited to ensure the stability [5]. Clarys et al. [13] are among the earliest researchers to describe the main muscles involved in archery training which include the trapezius, extensor digitorum, brachioradialis, triceps brachii, deltoid and biceps brachii muscles [13]. Another study by Lin et al. [14] recommended that stability of archery can be achieved with stable shoulder muscular activation [14]. This study on the other hand provides further evidence that the upper body muscles involved in shoulder abduction, adduction, flexion and extension as well as elbow extension are significantly stronger in those with archery training as compared to those without archery training. Although electromyographic evidence pointed to the importance of certain muscles contraction to achieve good accuracy in archery, the effect of the training is believed to enhance strength of other neighbouring muscles, hence increasing the upper body muscle strength in general [13, 14]. Preserving muscle integrity of lower extremities is essential in preventing disability, physical frailty and dependency that occurs due to aging. The significance to maintain muscle strength of the lower body leads to recommendation of various types of exercise such as squats, leg extension, step -up, jumps and lunges exercise [15]. Activities such as squats and 1-Repetition Maximum (1RM) for lower body proved to have significant impact in increasing muscle strength of lower body primarily the gluteus, adductor, quadricep and hamstring group of muscles. All these exercises or sports related to the described activities suit the young healthy individuals. However, there is an increased risk of injuries for these activities to be practiced by elderly and those with physical disabilities and health problems [16, 17]. The striking effects of archery on groups of muscles involved in hip abduction and adduction as well as knee extension in this study demonstrate that archery training is a potential activity to promote lower body strength with minimal risk of injury. Available data suggests that the prevalence of inactive population in the world is 31% [18]. Surprisingly, Lian et al. [19] reported that 60% of Malaysian adults are classified as sedentary [19]. Restricted physical activity will alter muscle metabolism that leads to early muscle fatigue in young adults. Both isokinetic and isometric exercises are found to increase muscle resistance to fatigue, muscle mass and strength, and the proportion of type I muscle fibers [20, 21]. Therefore, archery as one of the isometric or static sports may serve as an alternative physical activity for young adults who have the least interest on isokinetic sports. Above all else, the training for archery can be performed either outdoor or indoor, thus the activity suits any types of weather. Previous studies also pointed out that archery is a recommended safe sport to improve flexibility in patients with haemophilia and ischaemic heart disease [22, 23]. Reduced muscle strength is directly related to loss of muscle mass or atrophy. Despite the fact that there is an age-related decline in muscle mass and strength, previous studies reported that the decline has highly resulted from decreasing physical activity with age. Well-trained senior athletes showed similar regression of their muscle mass, however the regression is slower compared to those who are inactive [24].
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Normal age-related physiological changes such as loss of spinal motor neurons and motor units, redistribution of fast and slow muscle fibers, and reduction of hormones such as growth hormones and androgens are factors that limit physical activities in aging. Therefore, as a slower pace of dynamic physical activities are recommended for elderly, adding static sport such as archery that benefits muscle strength may delay undesirable health limitations due to muscle problems in elderly [2, 25]. The limitation of this study includes poor participation of youth in archery training within the desired age range. Most of the youth approached for this study are involved in archery training for professional tournaments whereby, other specific trainings are also given to increase their muscle strength.
5 Conclusion In conclusion, training in archery has significant impacts on the muscle strength of both the upper and lower body in youths. Archery as a type of sport or training warrants more attention as this physical activity is proven to maintain healthy muscles in preparation of our advancing age. This study serves as the baseline that provides evidence on the health benefits brought by archery training. Future studies involving archery intervention in different age groups and physiques should seriously be considered. Acknowledgements. We wish to acknowledge the participants in this study, archery clubs and the collaborating universities. We also acknowledge the technical help and support by the laboratory assistants and scientific officers involved. This work was supported by the Malaysian Ministry of Higher Education Grant, grant number: FRGS-FPSK-51415-50 and the Universiti Sains Islam Malaysia Grant, grant number: USIM/UKM/RCRP/FPSK/052002/71017.
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7. Leblanc, A., Pescatello, L.S., Taylor, B.A., Capizzi, J.A., Clarkson, P.M., Michael White, C., et al.: Relationships between physical activity and muscular strength among healthy adults across the lifespan. SpringerPlus 4, 557 (2015) 8. Abe, T., DeHoyos, D.V., Pollock, M.L., Garzarella, L.: Time course for strength and muscle thickness changes following upper and lower body resistance training in men and women. Eur. J. Appl. Physiol. 81(3), 174–180 (2000) 9. Dowman, L., McDonald, C.F., Hill, C.J., Lee, A., Barker, K., Boote, C., et al.: Reliability of the hand held dynamometer in measuring muscle strength in people with interstitial lung disease. Physiotherapy 102(3), 249–255 (2016) 10. Samosawala, N.R., Vaishali, K., Kalyana, B.C.: Measurement of muscle strength with handheld dynamometer in intensive care unit. Indian J. Crit. Care Med.: Peer-Rev. Official Publ. Indian Soc. Crit. Care Med. 20(1), 21–26 (2016) 11. Sanchis-Moysi, J., Idoate, F., Olmedillas, H., Guadalupe-Grau, A., Alayón, S., Carreras, A., et al.: The upper extremity of the professional tennis player: muscle volumes, fiber-type distribution and muscle strength. Scand. J. Med. Sci. Sports 20(3), 524–534 (2010) 12. Bencke, J., Damsgaard, R., Saekmose, A., Jørgensen, P., Jørgensen, K., Klausen, K.: Anaerobic power and muscle strength characteristics of 11 years old elite and non-elite boys and girls from gymnastics, team handball, tennis and swimming. Scand. J. Med. Sci. Sports 12(3), 171–178 (2002) 13. Clarys, J.P., Cabri, J., Bollens, E., Sleeckx, R., Taeymans, J., Vermeiren, M., et al.: Muscular activity of different shooting distances, different release techniques, and different performance levels, with and without stabilizers, in target archery. J. Sports Sci. 8(3), 235–257 (1990) 14. Lin, J.-J., Hung, C.-J., Yang, C.-C., Chen, H.-Y., Chou, F.-C., Lu, T.-W.: Activation and tremor of the shoulder muscles to the demands of an archery task. J. Sports Sci. 28(4), 415– 421 (2010) 15. Gergley, J.C.: Comparison of two lower-body modes of endurance training on lower-body strength development while concurrently training. J. Strength Cond. Res. 23(3), 979–987 (2009) 16. Peate, W.F., Bates, G., Lunda, K., Francis, S., Bellamy, K.: Core strength: a new model for injury prediction and prevention. J. Occup. Med. Toxicol. 2(1), 3 (2007) 17. Schlicht, J., Camaione, D.N., Owen, S.V.: Effect of intense strength training on standing balance, walking speed, and sit-to-stand performance in older adults. J. Gerontol.: Ser. A 56 (5), M281–M286 (2001) 18. Kohl, H.W., Craig, C.L., Lambert, E.V., Inoue, S., Alkandari, J.R., Leetongin, G., et al.: The pandemic of physical inactivity: global action for public health. Lancet 380(9838), 294–305 (2012) 19. Cai Lian, T., Bonn, G., Si Han, Y., Chin Choo, Y., Chee, P.W.: Physical activity and its correlates among adults in Malaysia: a cross-sectional descriptive study. PLoS ONE 11(6), e0157730 (2016) 20. Amann, M., Sidhu, S.K., Weavil, J.C., Mangum, T.S., Venturelli, M.: Autonomic responses to exercise: group III/IV muscle afferents and fatigue. Auton. Neurosci. Basic Clin. 188, 19– 23 (2015) 21. Bogdanis, G.C.: Effects of physical activity and inactivity on muscle fatigue. Front. Physiol. 3, 142 (2012) 22. Borjesson, M., Assanelli, D., Carre, F., Dugmore, D., Panhuyzen-Goedkoop, N.M., Seiler, C., et al.: ESC study group of sports cardiology: recommendations for participation in leisure-time physical activity and competitive sports for patients with ischaemic heart disease. Eur. J. Cardiovasc. Prev. Rehabil.: Official J. Eur. Soc. Cardiol. Working Groups Epidemiol. Prev. Card. Rehabil. Exerc. Physiol. 13(2), 137–149 (2006)
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23. Heijnen, L.: The role of rehabilitation and sports in haemophilia patients with inhibitors. Haemophilia 14(s6), 45–51 (2008) 24. Karavirta, L., Häkkinen, A., Sillanpää, E., García-López, D., Kauhanen, A., Haapasaari, A., et al.: Effects of combined endurance and strength training on muscle strength, power and hypertrophy in 40–67-year-old men. Scand. J. Med. Sci. Sports 21(3), 402–411 (2011) 25. Tomas-Carus, P., Ortega-Alonso, A., Pietilainen, K.H., Santos, V., Goncalves, H., Ramos, J., et al.: A randomized controlled trial on the effects of combined aerobic-resistance exercise on muscle strength and fatigue, glycemic control and health-related quality of life of type 2 diabetes patients. J. Sports Med. Phys. Fitness 56(5), 572–578 (2016)
The Effect of Zone, Gender, RAE and Fitness Variables Towards Fitness Status and Anthropometric Attributes of Children in Malaysia Ahmad Bisyri Husin Musawi Maliki1, Mohamad Razali Abdullah1(&), Siti Musliha Mat-Rasid1, Hafizan Juahir1, Mohd Syaiful Nizam Abu Hassan2, Nik Naleesa Nasuha Rusmadi2, Muhammad Ziyad Yazid2, Fatin Zulaikha Azmin2, Tengku Nur Arnie Tengku Ghazali2, Amr Salem Falah1, Muhammad Rabani Hashim1, and Rabiu Muazu Musa3 1
East Coast Environmental Research Institute, Universiti Sultan Zainal Abidin, Gong Badak Campus, 21300 Kuala Terengganu, Terengganu, Malaysia [email protected] 2 Faculty of Applied Social Sciences, Universiti Sultan Zainal Abidin, Gong Badak Campus, 21300 Kuala Terengganu, Terengganu, Malaysia 3 Centre for Fundamental and Liberal Education, Universiti Malaysia Terengganu, 21030, Kuala Nerus, Terengganu, Malaysia
Abstract. This research aims to identify the influence of zone, gender, RAE, and fitness performance variables and their relationship with physical fitness and anthropometric attributes of Malaysian children. Data were obtained from 43607 participants aged 7 years old in Malaysia. The participants completed the multiple of test (anthropometrics, standing broad jump, twenty-meter speed, sit and reach and hand wall toss). Data interpretation was carried out using analysis of variance as well as principal component analysis (PCA). The PCA was computed to determine the appropriate components with an eigenvalue greater than 1 (eigenvalue > 1.0). Further analysis performed with varimax rotation demonstrated that some domain variables are able to distinguish children performances. The finding indicates that high performance children are attributed to considerable higher anthropometry and are lacking in flexibility as well as leg and hand strength amongst other variables (p < 0.05). The overall findings revealed that zone, gender, RAE, fitness, and anthropometry do have an influenced toward children physical fitness performance in Malaysia. Keywords: Zone
RAE Gender Fitness Children
1 Introduction Technology and telephone have become an important part of the daily activities for the community in modern countries. This is because mobile technology has the essential functions needed for family life. Many children are currently exposed to this © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 257–267, 2020. https://doi.org/10.1007/978-981-15-3270-2_28
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technology. In the childhood phase, the parents and the surroundings greatly influence the habits and patterns of children’s activities [1]. Uncontrollable technology use among children can lead to bad habits like obsession with social media apps and digital games [2]. Nowadays children are currently growing up through different exposures with technology as opposed to the children of the past generation. Significant differences can be seen in terms of greater opportunities in exploring the world, spending more time on television and video game and lack of holistic self-development due to the domestic landscape that directly linked to the rapid and widespread development and access of new media technologies [3]. In the unconscious, children are currently inactive due to an unhealthy lifestyle and it contributes to low fitness performance. Low fitness performance can lead to a variety of diseases and obesity which has become prevalent among the children of the present generation. It was reported that approximately about 170 million children are obese worldwide [4]. There are 12.7% of children in Malaysia are obese which placed Malaysia as the second highest in Asia after Brunei [5]. Obesity can affect health and social problem in short-term and long-term [6]. Even though the risk of obesity among children is less noticeable, obesity problems during childhood will contribute to a variety of health problems when the child is growing up. Obesity among children is a serious crisis and it contributes to chronic illness, disability, and premature death [7]. Obesity among Malaysian school students has shown that the distribution of obesity is different for students living in urban areas with rural areas where students who are living in rural areas have shown a lower percentage of obesity. Another study found that primary school boys had a higher percentage of overweight problems compared to female students [8]. In addition, students who are always exercising and engaging in school sports activities have shown a lower percentage of overweight and obesity problems than students who are inactive in school sports [9]. Furthermore, the Relative Age Effect (RAE) can affect the physical attribute and motor fitness level. The possibility of RAE factors can be used as a factor to contributing to harmful illnesses such as obesity. A study related to RAE on the physical fitness level, performance, and fitness of children was carried out by the previous researchers. Respondents were divided into 4 groups according to the month of birth. First group (January, February, and March), second group (April, May, and June), third group (July, August, and September) and fourth group (October, November, and December). The result shows that the first group showed higher performance quality compared to all other groups in the examined variables [10]. Another study found that a lack of physical activity is one of the main causes of obesity problems among children. So it leads to a deterioration of fitness and motor performance [11]. The present study, therefore, aims to identify the influence of zone, gender, RAE and fitness performance and their relationship to physical fitness and anthropometric attributes of children in Malaysia.
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2 Material and Method 2.1
Area of Study
This study had analyzed data on physical fitness among children in Malaysia. It involved 370 primary schools in West Malaysia; while in East Malaysia the schools involved are 217 primary schools. These schools comprise of National Schools (SK), Religious Schools (SA), Chinese National Type Schools (SJK (C)) and Tamil National Type Schools (SKJ (T)). This child’s age is 6 to 7 years old. In the West of Malaysia, boys are 15266 while in Eastern Malaysia is 8749; girls in West Malaysia are 12217 and in East Malaysia is 7375. The data are in conjunction with the Ministry of Education Malaysia aimed at monitoring the fitness level of children aged 6 to 7 years old. 2.2
Participants and Testing Procedure
A total of 24015 boys were enrolled from 587 primary schools while the girls selected to take the test were 19592 in Malaysia. They are tested using some anthropometric components (current age, weight, height, zone, BMI, RAE and gender); and four motor subscales such as flexibility, coordination, speed, and power. The procedures for anthropometric measurements and motor fitness tests of children in this study were carried out as follows. Prior to data collection, informed consent was given to parents, guardians, school authorities and participants to explain a few things such as research procedures, research objectives, and others. Participants who agree to participate voluntarily are considered for data collection. In the consent form, some of the main sections that participants need to fulfill as participants’ personal information and contact detail; emergency contact information; medical information and confirmation of parent’s consent. This information is for research purposes only. All personal information was not disclosed by the researcher. Anthropometrics For a basic measurement of weight and height, the tools used are like a stadiometer and a weighing scale. Feature of height was measured to the nearest 0.1 cm, and the feature of mass was measured in kg. The height is measured from the foot to over the head while standing with the rear position placed on the flat wall and the arms folded with the palms facing the investigator. The required tool consists of a tape measure on the wall, measured in centimeters (cm). Standing Broad Jump (SBJ) The participants have to stand behind a line marked on the ground with feet slightly apart. A two-foot take-off and landing were used, with swing the arms back and rhythmically bending the knees to about 90 degrees forward. The participants need to try to jump as far as possible, landing on both feet without falling backward. This test (SJB) will be canceled if the participants making the mistake which is doing the double jumping and step on the line before jumping. Three trials were allowed and the furthest was considered.
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Twenty-Meter Speed Test (20MR) The participants running a single maximum sprint over a set range, with the recorded occasion. The distance between the starting point and the end was 20 m. When either foot passed the starting point, the time began to count and completed once either foot passed the finishing point. Before the test, participants have to make sure the starting position should be standardized, starting from a stationary position with a foot back the starting point, without making any movements. By using stopwatch thing, the time to run each split distance (20 m) was measured. Sit and Reach (SAR) The participants sitting on the floor with straight legs, with heels on the floor and feet flat against the seat and reach the box. Both sides of the knees are held flat against the floor by the investigator if needed. With hands-on top of each other and palms facing down, the participants will then smoothly reached forward with fingertips pushing the measuring slide across the measuring line as far as possible. The reach is held for at least two seconds while the distance is taken. The investigator has; make sure there are no jerky movements and the fingertips remain level with the legs flat. Readings must be taken in multiples of 0.5 cm. Hand Wall Toss (HWT) The distance between the markers, it is 1 m away from the wall. The participants have to stands upright behind a marker line and facing the wall. The ball is thrown by one hand by making an underarm action against the wall and trying to catch the ball using the opposite hand. The ball is then thrown to the back of the wall and captured with the first hand. This test persists for 10 attempts. The number of throws that were caught will be recorded. 2.3
Statistical Analysis
Pre-Processing Data A set of 305249 matrix data (7 variables 43607 datasets) is calculated in this analysis. The amount of missing data in the matrix is very small (*3%) compared to the recorded data overall [12]. Hence, the nearest neighboring techniques have been used in this study to replace missing data and errors due to its simplicity and effectiveness. This technique is to examine the distance between each lost data and the closest distance to it. The nearest neighboring method is the simplest method, where the last distance is used as an estimate of all lost values [13–17]. Principal Component Analysis (PCA) This is important to test if the sample size is large enough and good for the Principal Component Analysis (PCA). PCA is unmatched and great if the results of the correlation matrix are identified matrix. The data is appropriate for extracting these factors [18]. The eigenvalues of the correlation matrix are calculated using the extraction of those factors. Standard coefficients by selected factors have been used to develop a child’s physical health model. The basic component (PC) can be measurable by the equation whereas z is the component score, a is the component load, x is the estimated
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parameter value, i is the number of components, j is the number of participants and m is the sum of the cumulative parameters [19]. zij ¼ ai1 x1j þ ai2 x2j þ . . . þ aim xmj
ð1Þ
Analysis of Variance (ANOVA) Before start analyzing the data of anthropometric components (RAE, gender, and zone), an intra-class correlation coefficient; analysts have conducted reliability analysis to ensure the authenticity and validity of the data obtained [20]. Children’s fitness levels are measured through motor fitness tests (flexibility, coordination, power, and speed). Children’s fitness level results were used to analyze the data through ANOVA with confidence level p 0.05 [21]. Anthropometrics (RAE, gender, and zone) are used as dependent variables (DV) meanwhile motor fitness tests are used as the independent variable (IV). Scatter diagram shows the parameter of the physical fitness of children based on anthropometric components and motor fitness test. Data for 43607 participants were analyzed and evaluated using the SPSS version 20.0 for Windows.
3 Results and Discussion The output of this study is projected in two-fold, (1) examine the domain components interrelated to the fitness performance and (2) scrutinize group differences of BMI, zone, gender, index and RAE toward a child’s fitness performance. Before the main analysis, PCA was computed to determine the appropriate components with an eigenvalue greater than 1 (eigenvalue > 1.0). It can be observed from Fig. 1 that PCA identified two components as the most essential due to the higher eigenvalues (>1). Further analysis performed with varimax rotation by applying two new latent factors in the manner of the appropriate interpretation. After varimax rotation, the PCA pattern displayed in Table 1. The effect of the variance can be seen 32.2% for PCA1 and PCA2 (24.2%) with the cumulative of variance is 56.4%. From the first factors (PCA1) three principal components have satisfied the factor loading threshold (factor loading threshold > 0.65) which is weight, height, and BMI. The three-factor is reflecting the high fitness performance. Fitness performance in the child needed to be observed as it has associated with the importance of weight, height, and BMI. According to past studies, when the child is growing up, the obesity problem will provide a variety of health problems [7]. Meanwhile, the different domain components which are, power and speed of the second factors will be explained. This discovery suggesting the domain factors of fitness performance. Variation of the zone, gender, RAE and fitness performance were further discussed. Additionally, by applying the output of the PCA, further analysis was calculated by acquiring an index of the fitness. Table 2 shows three different categorical sets of fitness namely low, moderate and high fitness index based on the most dominant components considered. Based on an index described 216 children consist of a high fitness index group while 41,314 children on moderate and 2076 children on low fitness index group. With regards to the result of the fitness index, each group was further analysed in order to seek the variation on the fitness performance.
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Scree plot
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Fig. 1. Scree plot of descriptive eigenvalue Table 1. Factor loading pattern after Varimax rotation (factor loading set at >0.65) Component Weight (kg) Height (cm) BMI (kg/m2) Power (cm) Speed (saat)
PCA 1 PCA2 0.99 0.67 0.87 0.78 0.72
Eigenvalue 2.25 Variability (%) 32.20 Cumulative % 32.20
1.70 24.22 56.43
Table 2. Index status of fitness index Status Frequency Cum. frequency % 0.0 2076 2076 4.8 25.0 41314 43390 94.7 75.0 216 43606 0.5
Fitness index Group range LFI .0 low < 25.0 MFI 25.0 Moderate < 75.0 HFI High 75.0
By applying ANOVA, the output of an index was further analyzed to determine the differences between variables (RAE, zone, gender, BMI and Index). In Table 3, the fitness of the children that classified as high, moderate and low in the index are summarized. High index performance is significantly lacking flexibility, ability to quickly perform, leg and hand power, and have equivalently higher body size (height
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and weight) which is (p < 0.05). The result in Tables 4 and 5 show the same result but in Table 6 one groups do not differ in speed (p > 0.05). The discrepancy of the fitness performance based on the significant parameters are summarized in Table 3.
Table 3. Fitness status of the children classified as high, moderate and low in index Variables High Moderate Low Pr > F Weight (kg) 48.80 23.19 17.22 0.001 Height (cm) 134.34 120.13 111.92 0.001 Power (cm) 103.10 102.78 81.91 0.001 Flexible (cm) 29.23 26.85 23.84 0.001 Coordination (no.) 7.29 5.30 2.35 0.001 Speed (saat) 4.91 4.93 5.84 0.001 BMI (kg/m2) 27.42 15.97 13.80 0.001
Significant Yes Yes Yes Yes Yes Yes Yes
According to the results shown in Table 3, children in Malaysia have a moderate level of physical fitness. Participants significantly show moderate performance results in every test. This result is similar to some studies that found the level of physical fitness of children in Malaysia is moderate due to the moderation of government program policy in schools [22]. The Factors include a shortage of qualified sports subject teachers, low student engagement, high-quality students and student enthusiasm. These factors have shown a significant impact on children’s physical fitness. Another study found that the location of residential areas is significantly related to the level of children’s fitness [23]. Children who live in rural areas have higher fitness performance than children living in cities due to exposure to technology, social conditions in housing areas, pollution, social problems, public amenities and so on. Based on the results shown in Table 4, boys have higher fitness performance than girls. The study also supports the results of this study [24]. However, it is slightly different from another study that found the girls performed better in physical fitness in terms of jumping and balance than boys. On the other hand, the boys showed better fitness performance in catching and receiving the ball. Gender differences in physical fitness will change over time as physical fitness performance is influenced by training factors, opportunities, family expectations and needs in a particular environment. Whereas found that gender differences in physical fitness are increasing over time, as physical fitness performance is influenced by factors of opportunity, family expectations, and needs in a given environment [25]. Based on the result shown in Table 5, children who born at an early-month birth has the highest level of physical fitness. The RAE contributes to the majority of children born at the early-month birth and has a high level of physical fitness compared to the next month [26]. Some pieces of evidence show earlier mature children, usually have a high-level fitness [27]. Also, RAE can show differences in the growth and development of children. This table shows that all the results are in a significant group, children in the Q1 has more ability to do fitness tests compared to Q4. The application
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A. B. H. Musawi Maliki et al. Table 4. Fitness status of the children classified based on gender Variables Boys Girls Weight (kg) 23.34 22.65 Height (cm) 120.06 119.51 Power (cm) 107.24 95.11 Flexible (cm) 26.55 26.92 Coordination (no.) 5.78 4.43 Speed (saat) 4.81 5.17 16.06 15.75 BMI (kg/m2)
Pr > F Significant 0.00 Yes 0.00 Yes 0.00 Yes 0.00 Yes 0.00 Yes 0.00 Yes 0.00 Yes
Table 5. The fitness level of the children classified based on RAE Variables Q1 Q2 Q3 Q4 Weight (kg) 23.99 23.34 22.68 21.99 Height (cm) 121.69 120.48 119.09 117.76 Power (cm) 104.27 102.64 100.95 98.99 Flexible (cm) 26.78 26.74 26.74 26.59 Coordination (no.) 5.64 5.32 5.02 4.65 Speed (saat) 4.90 4.95 4.99 5.06 16.07 15.96 15.87 15.76 BMI (kg/m2)
Pr > F Significant 0.00 Yes 0.00 Yes 0.00 Yes 0.04 Yes 0.00 Yes 0.00 Yes 0.00 Yes
Table 6. The fitness level of the children classified with respect to zone Variables West Malaysia East Malaysia Weight (kg) 23.16 22.81 Height (cm) 120.48 118.68 Power (cm) 101.25 102.71 Flexible (cm) 26.52 27.04 Coordination (no.) 5.25 5.04 Speed (saat) 4.97 4.97 2 15.85 16.04 BMI (kg/m )
Pr > F Significant 0.00 Yes 0.00 Yes 0.00 Yes 0.00 Yes 0.00 Yes 0.67 No 0.00 Yes
has shown to be significant between the zones in children’s fitness performance in Table 6. In East Africa where many populations are swiftly transitioning from an agrarian to an industrialized economy, urban children are more inactive and have promptly weight compared to country children [28]. Here we find that east and west Malaysia children have noticeable differences in body growth and adiposity but few differences in terms of fitness performance. As some authors have discussed, this is especially significant because physical fitness may be a stronger predictor of cardiovascular health and disease risk than activity levels [29]. This result recommends that there may be rare epidemiological risks of urbanization in expand countries where
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physical fitness is possibly changing at a different rate than activity levels. A different explanation to be tested is that the urban groups studied here were able to maintain high activity levels to be as physically fit as the rural group, despite measured differences in body composition.
4 Conclusion Based on the findings of the present study, it is clear that girls who are born in the fourth quarter of the year and living in West Malaysia have a considerable low fitness status. This concern is heightened when some studies reported that current children in Malaysia are the second most obese children in ASEAN [30]. This study can be an important reminder for an important issue for parents and other stakeholders to address. The effective measure is to keep their children fit and live an active lifestyle. These suggestions can help children to live healthier lives. Besides, regular health check-up is encouraged especially for obese children. The researchers recommended that early measured should be taken in order to prevent the prevalence of an inactive lifestyle of children in Malaysia by encouraging more physical activity and provision of adequate sporting facilities in schools to engage students to partake in various physical activity. Acknowledgments. Sultan Zainal Abidin University (UniSZA) have collaborated with Terengganu State Sports Council (MSNT) and National Sports Institute (ISN) to obtain the data about physical fitness among children. Terengganu State Sports Council (MSNT) and National Sport Institute (ISN) has provided a grant for this research. Number of grant (i1017-00005). This institute providing full of support for this research. The researchers would like to thank parents, guardians, schools authorities and participants for the good cooperation in the success of this research.
References 1. Talib, R.A., Lim, S.H., Fakhrurazi, H., Buhari, S.S., Poh, B.K.: Penilaian Media Bercetak Untuk Pendidikan Pemakanan Kanak-Kanak Berlebihan Berat Badan Dan Obes. Jurnal Sains Kesihatan Malaysia 11, 55–62 (2013) 2. Omar, A.: Permainan Mudah Alih Dan Kanak-Kanak. Idealogy 2, 137–149 (2017) 3. Abas, W.A., Hamzah, A.: Media Dalam Kehidupan Dan Perkembangan Kanak-Kanak. Jurnal Pengajian Media Malaysia 15, 27–39 (2013) 4. WHO: Population-Based Approaches to Childhood Obesity Prevention. World Health Organization, Geneva (2012) 5. WHO: Global Health Observatory Data. Who Health Organization, 10 July 2019. https:// www.who.Int 6. Sri Dhyanaputri, I.G.A., Hartini, Th.N.S., Kristina, S.A.: Persepsi Ibu, Guru Dan Tenaga Kesehatan Tentang Obesitas Pada Anak Taman Kanak-Kanak. Berita Kedokteran Masyarakat 27, 32–40 (2011) 7. Kasmini, K., Idris, M.N., Fatimah, A., Hanafiah, S., Iran, H., Asmah Bee, M.N.: prevalence of overweight and obese school children aged between 7 to 16 years amongst the major 3 ethnic groups in Kuala Lumpur, Malaysia. Asia Pac. J. Clin. Nutr. 6, 172–174 (1997)
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23. Joens-Matre, R.R., Welk, G.J., Calabro, M.A., Russell, D.W., Nicklay, E., Hensley, L.D.: Rural-urban differences in physical activity, physical fitness, and overweight prevalence of children. J. Rural Health 24(1), 49–54 (2008) 24. Hashim, A.: Prestasi kemahiran asas motor dan kecergasan fizikal murid tahap II sekolah rendah (Doctoral dissertation, Universiti Pertanian Malaysia), pp. 1–24 (1994) 25. McKenzie, T.L., Sallis, J.F., Broyles, S.L., Zive, M.M., Nader, P.R., Berry, C.C., Brennan, J. J.: Childhood movement skills: predictors of physical activity in Anglo American and Mexican American adolescents? Res. Q. Exerc. Sport 73(3), 238–244 (2002) 26. Helsen, M., Vollebergh, W., Meeus, W.: Social support from parents and friends and emotional problems in adolescence. J. Youth Adolesc. 29(3), 319–335 (2000) 27. Baker, J., Schorer, J., Cobley, S.: Relative age effects. Sportwissenschaft 40(1), 26–30 (2010). [8] Nolan, J.E., Howell, G.: Hockey success and birth date: the relative age effect revisited 28. Muthuri, S.K., Francis, C.E., Wachira, L.J.M., LeBlanc, A.G., Sampson, M., Onywera, V. O., Tremblay, M.S.: Evidence of an overweight/obesity transition among school-aged children and youth in Sub-Saharan Africa: a systematic review. PLoS ONE 9(3), e92846 (2014) 29. Sassen, B., Cornelissen, V.A., Kiers, H., Wittink, H., Kok, G., Vanhees, L.: Physical fitness matters more than physical activity in controlling cardiovascular disease risk factors. Eur. J. Cardiovasc. Prev. Rehabil. 16(6), 677–683 (2009) 30. World Health Organization: Basic Concepts for Capacity-Building. Research Ethics Committees (2019)
Sports Engineering and Technology
Offline LabVIEW-Based EEG Signals Analysis to Detect Vehicle Driver Microsleep N. Sulaiman(&)
, K. S. Goh, M. Rashid, S. Jadin, M. Mustafa, M. Z. Ibrahim, and F. Samsuri
Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang, 26600 Pekan, Pahang, Malaysia [email protected]
Abstract. Microsleep is often known as unintended loss of attention and alertness within short period of time briefly between a second up to 30 s. Microsleep might be dangerous to vehicle driver especially for long-distance driver due to unawareness and loss of focus towards surrounding environment. Thus, microsleep detection system based on Electroencephalogram (EEG) signals is proposed in this research to prevent the drivers to involve in the accidents. For investigation purpose, six samples are chosen to obtain their brain signals using NeuroSky Mindwave Mobile Headset and eegID mobile application in two different states which are relax state for 5 min and driving state for 1 h. Besides, a Graphical User Interface (GUI) is constructed using LabVIEW to analyze the EEG signals. The captured EEG signals then, are undergone preprocessing to remove noises and undesired artifacts. Bandpass filter is then applied to brainwaves to split the signals into Alpha and Theta waves. The patterns of these waves are examined and analyzed using power spectrum technique to search for unique features that might relate to microsleep event. The kNN classifier is employed to classify the selected features in term of Standard Deviation (SD) and Spectral Centroid (SC). The best classification accuracy for SD and SC features are obtained at 82.83% and 77.65% respectively for 80:20 training-testing ratios. Besides, the analysis of EEG Alpha and Theta band using Short-Time Fourier Transform (STFT) technique able to localize the EEG signals to indicate the exact time of the microsleep occurrence. The alarm system and steering vibration motor are assembled and will be activated for any detection of microsleep event. Keywords: Microsleep event Vehicle driver Short-Time Fourier Transform (STFT)
EEG signals LabVIEW
1 Introduction 1.1
Background
The major concern for all the road users especially vehicle drivers all over the world are safety. However, the percentage of car accident has been increased year by year where Malaysia having the highest car accidents fatality risk (per 100,000 population) among the ASEAN countries [1]. Microsleep or lapse is one of the most significant causes in © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 271–289, 2020. https://doi.org/10.1007/978-981-15-3270-2_29
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Malaysia that leads to lethal road accidents as the drivers having loss of responsiveness and transient eye closure at the wheel. For further explanation, microsleep is a temporary episode of sleep which may last for a fraction of a second or up to 30 s where an individual fails to respond to some arbitrary sensory input and becomes unconscious [2]. It happens when an individual loses of attention and regains attention after a brief lapse in consciousness, or when there is a rapid shifting between wakefulness and drowsiness states. In terms of physiological, microsleep manifest as droopy eyes, slow eyelid closure, and head nodding [3] while microsleep is occurred when there is a shift in neural or cognitive activities from alert or awake cognitive state to sleep or light sleep cognitive state. 1.2
EEG Signals
EEG is the measurement of voltages on the scalp generated by ionic currents flowing in the brain’s neurons. The firing of neurons generates circulating ionic currents and an associated electric field, and an array of electrodes distributed over the scalp samples the potential in space and time [4]. Analysis and investigation of brain activity can be easily conducted by manipulating the collected EEG signal because EEG helps to illustrate the state the person is currently in whether is happy, nervous or even asleep [5]. However, this signal contains various frequency waves where each frequency band having its own characteristics and behavior. For instances, Alpha wave indicates the relaxation, Beta wave shows the alertness, Delta wave illustrates the deep sleepiness and Theta wave describes the drowsiness. The decrement of the Alpha band and the increment in the Theta frequency, produce drowsiness [5]. Table 1 shows the EEG signal with four major frequency bands to study about sleep stage. Table 1. EEG frequency bands with neural activity [6]. Sleep stage versus frequency Neural activity EEG band Deep sleep Delta Drowsiness Theta Resting, relaxed Alpha Alert Beta Hyperactivity Gamma
1.3
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Brain-Computer Interface (BCI)
Various researches have been done to communicate between the biomedical signals and outside world by applying brain-computer interface (BCI). BCI communication is very helpful as the signals produce by the brain activity can be extracted and processed to communicate with the external devices with almost no muscle movement. BCI can be classified to two main classes which are the invasive and the non-invasive type. The invasive type of BCI is that microelectrodes are implanted directly to into the grey
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matter of the brain through neurosurgery. Here, the highest quality of signals that generated by human’s body able to be collected by using this manner. Although the same method can be used to control external devices as well, but it is not preferable as implementing invasive BCI may cost more and put the individual at stack of risking himself to undergo the neurosurgery to implant the microelectrodes beneath the scalp in the grey matter. Therefore, the non-invasive BCI is introduced which does not require any surgery to implant devices into the body. The EEG headset measures the potential difference across electrodes in the headset. The standard EEG montage is according to the 10–20 system as shown in Fig. 1 which is an internationally recognized method to describe and apply the electrodes on the scalp.
Fig. 1. 10–20 Electrode placement system [7].
1.4
Research Objective
The main objective of this research is to develop a system to detect the vehicle driver’s microsleep event from the analysis of EEG signals. The sub-objective includes the development of LabVIEW block diagram (coding) to extract and analyze EEG features from EEG signals that might relates to microsleep event.
2 Methodology The research emphasizes on the construction of LabVIEW front panel and block diagram to analyze brainwaves of the drivers and monitor the cognitive state of the driver. Thus, several procedures are carried out as described below. 2.1
Subject Selection
The subjects are classified into two different categories based on their age. The age ranging 23–26 years consists of 3 males and one female while the age ranging from 45–50 years old consists of one male and one female which sum up a total of 6 subjects.
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EEG Measurement and Protocol
In this research, single channel Neurosky MindWave EEG headset as shown in Fig. 2 is selected to acquire the EEG signal of the chosen subjects at sampling rate of 512 Hz. The sensor tip of Neurosky is placed on the forehead, namely, FP1 position of the subject and the ear clip is clipped onto the earlobe. When Neurosky headset is turned on, it is automatically become a Bluetooth pairing mode. Then, the Bluetooth device (smartphone/laptop) is turned on to pair with the Neuosky Mindwave Mobile headset then open eegID application as shown in Fig. 3 to collect and record the data. Here, the captured EEG data from EEG amplifier is uploaded to the drop box before transferring them to LabVIEW.
Fig. 2. NeuroSky Mindwave Mobile headset.
Fig. 3. eegID mobile application.
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For measurement protocol, EEG data will be taken in 2 different state conditions which include relax state and driving state (using car simulator and real car). Before taking any measurements, subjects are instructed to relax and driving for 1 min before their EEG data are taken in relax state and driving state for 5 min and 60 min respectively. Then, the captured EEG data is transferred to LabVIEW through the drop box for analysis of microsleep in LabVIEW. In EEG montage set-up, the position of EEG electrodes at Fp1 is suitable since that position is associated with Frontal lobe which associated with human’s thinking, behavior and memory activities as illustrated by Fig. 4. The microsleep event might be originated from this brain lobe.
Fig. 4. Brain lobes with its functions [3].
2.3
EEG Signal Processing
The collected EEG signal contains many artifacts and noise which will affect the accuracy and efficiency of the project. Thus, signal pre-processing is implemented before proceeding to next procedures to detect microsleep event. The proposed design undergo two stages of the signal processing which are the set-up of 100 µV threshold voltage to eliminate the eye blink, eye movement and muscle movement artifacts [8] and then, implement bandpass filter with lower and upper cut-off frequency of 0.5 Hz and 50 Hz respectively to remove line noise (60 Hz) and high frequency noises [9, 10]. After the signal is processed, the signal is further classified to alpha waves and theta waves to detect microsleep event. It is done by applying two bandpass filter of frequency band 8–13 Hz and 4–7 Hz to get Alpha and Theta waves respectively. Next, Power Spectral Density (PSD) for both bands is calculated by performing Fast Fourier Transform (FFT) with Hanning window before proceeding to feature extraction stage. The window was set to 256 with 50% overlapping and the FFT length was set to 1024. Meanwhile, STFT is applied to provide the time-frequency analysis or time-frequency imaging of the Alpha and Theta band in order to track the occurrence of microsleep event in term of time and frequency. 2.4
Feature Extraction
In this study, Standard Deviation and Spectral Centroid of EEG signal are selected as the features in microsleep detection. The Spectral Centroid is defined as the average
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frequency weighted by amplitudes, divided by the sum of the amplitudes. The formula to calculate Spectral Centroid is shown in Eq. 1 [11]. However, Standard Deviation is defined as a statistical feature which indicates the distribution of the data with respective to the mean. The formula to calculate Standard Deviation is shown in Eq. 2 where µ represents the mean or average, and N denotes length of EEG data. R xgð xÞdx SC ¼ R gð xÞdx sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi P jx lj2 SD ¼ N
ð1Þ
ð2Þ
The Standard Deviation and Spectral Centroid are applied to the power spectrum of EEG Alpha and Theta bands in order to find the microsleep parameter when there are changes in the neural states due to the implementation of different exercises et.al relax state and driving state. The power spectrum of EEG signals is calculated using Fourier transform and power spectral density techniques in LabVIEW. The equation of the power spectrum and power spectral density is shown in Eqs. 3 and 4 respectively where x(n) represents the EEG data, N denotes the length of EEG data and TS is the sampling period. X ðk Þ ¼
XN1 n¼0
xðnTsÞe
j2pnk N
;
k ¼ 0; 1; . . .; N 1
XN1 j2pnk 2 PSD ¼ jX ðk Þj2 ¼ n¼0 xðnTsÞe N
2.5
ð3Þ ð4Þ
Short Time Fourier Transform (STFT)
In analyzing EEG signal, the cleaned and filtered EEG signals were formed into spectrogram images using Short Time Fourier Transform (STFT) technique. Here, the STFT is generated by multiplying the shifting window function, Wn with the Fourier Transform of the EEG signal [12, 13]. The form of the spectrogram image is based on the selected frequency bands which are Alpha and Theta bands. The Fourier Transform shows the frequency content of the signal after applying FFT on the EEG signal. However, this technique has yet to provide any information on the time components that appeared. Hence, to perform time-frequency analysis of EEG signal using STFT, a large time non-stationary EEG signal is divided into smaller segments with equal length and shifted using shifting window function with the time period of Sn and k as an integer. Then, the Fourier transform is applied to each shorter segment individually. The STFT formula is presented in Eq. 5. X ðk; ixÞ ¼
X þ 1 1
X þ 1 xðnÞ expðjnxÞ Wn ð n k Sn Þ exp ð jnx Þ ð5Þ 1
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The kNN uses a distance of features in a data set to determine which data belongs to which group. A group is formed when the distance within the data is close while many groups are formed when the distance within the data is far [14]. In other words, the classifier finds the k neighbourhood in the training data and assign group which appear more frequently in the neighbourhood of k as illustrated by Eq. 6. The value of k needs to be varied in order to find the match class between training and testing data. The default value of k is 1. The default neighbourhood setting is “Euclidean” and “nearest”. The “Euclidean” distance is used to find the object similarity in the k neighbourhood as shown in Eq. 6. dðXi ; Xj Þ ¼
rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi X ðXi ; Xj Þ2
ð6Þ
i
In this study, the default value of k is applied and the training and testing data is tested with 50:50 ratios, 60:40 ratios, 70:30 ratios and 80:20 ratios to obtain the highest microsleep classification accuracy. Beside the k value and training and testing ratio, the classifier default settings are changed in order to find the best setting that able produce high accuracy classification rate. 2.7
Flowchart and Block Diagram of the Study
The overall flowchart and block diagram of the study is shown in Figs. 5 and 6 respectively. After obtaining the EEG data from all the samples, the data is transferred into LabVIEW for EEG signals analysis in frequency domain. The EEG signals can be segregated into of five different frequency bands including Delta, Theta, Alpha, Beta and Gamma waves. However, only Alpha and Theta waves are extracted and used for investigation for microsleep in this study. In feature extraction stage, Power Spectral Density (PSD) is calculated and obtains the power spectrum of Alpha band and Theta band. Some other EEG feature extractions are investigated to search for the best EEG features to indicate the presence of microsleep event such as Standard Deviation, Spectral Centroid, Energy Spectral Density, Mean, and Entropy. However, only Standard Deviation and Spectral Centroid are selected and classified in this research to indicate the presence of microsleep event. After selecting the feature extraction method, microsleep is detected when a 3–14 s episode during which 4–7 Hz (theta) activity replaces the waking 8–13 Hz (Alpha) background rhythm [15]. When the parameter is met, the signal is classified as microsleep and then alarm system and steering vibration motor will be activated. Next, LabVIEW front panel or GUI is constructed to display the raw EEG signal, filtered signal, power spectrum of Alpha band and Theta band for performance analysis, plot of spectrogram (time-frequency imaging) and the microsleep event indicator.
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Fig. 5. Overall block diagram for microsleep detection system.
Fig. 6. Block diagram for microsleep detection system.
3 Results and Discussion The research consists of several stages such as the development of the LabVIEW block diagram to analyze the capture EEG signals in term of power spectrum, extract and classify the selected EEG features in term of standard deviation and spectral centroid, perform time-frequency analysis of the EEG Alpha and Theta power spectrum and finally to develop the Graphical User Interface (GUI) to display the analysis results and the status of the microsleep event.
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Overall LabVIEW Block Diagram
This section describes the construction of the overall LabVIEW block for the microsleep signal analysis and the set-up LabVIEW Interface for Arduino (LIFA) in order for LabVIEW to communicate with external devices as shown in Fig. 7. The process is started by reading the acquired EEG data of subjects in excel file using Read Delimited Spreadsheet. vi to import the .csv file into the LabVIEW after user has entered the file path as elucidated by Fig. 8. The Read Delimited Spreadsheet.vi is connected to Index Array to only import the desired EEG data column in .csv file which is eegRawValueVolts. Next, the waveform graph named as raw EEG is plotted before applying −100 µV to 100 µV signal remover looping and again the signal is plotted using waveform graph. Next, the 2nd order bandpass filter with lower and upper cut-offfrequency of 0.5 Hz and 50 Hz respectively is implemented to the filtered EEG data and plot the signal after applying bandpass filter with waveform graph as well as illustrated by Fig. 9. Then, create a Build Waveform with sampling frequency of 52 Hz and perform power spectral density (PSD) and Short-Time Fourier Transform simultaneously to get the overall power spectrum and spectrogram (time-frequency analysis) of the subject respectively as shown in Figs. 10 and 11. From the overall power spectrum, another 2nd order bandpass filter with 4 Hz lower cut-off frequency and 7 Hz upper cut-off frequency to obtain power spectrum of theta band and the same filter is applied but with 8 Hz lower cut-off frequency and 13 Hz upper cut-off frequency to acquire power spectrum of alpha band for microsleep analysis purpose. The bottom part of the block diagram is the output triggering section to display the mind status and microsleep indicator LED and activate alarm and vibrating motor using LIFA when microsleep event does take place. The overall block diagram of the LabVIEW to implement the microsleep detection system is shown in Fig. 12.
Fig. 7. Virtual Instrument (VI) package manager for LIFA.
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Fig. 8. Block diagram of importing EEG data and removing artifacts.
Fig. 9. Block diagram of obtaining the desired EEG frequency bands.
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The graphical user interface (GUI) is designed in LabVIEW to illustrate and display the results of EEG analysis. Figure 13 describes the overall LabVIEW GUI of the research. Here, the LabVIEW front panel is employed to display the raw EEG signals, filtered EEG signals, EEG frequency bands, Spectrogram plot of Alpha and Theta bands, EEG features extraction in term of Spectral Centroids of Alpha and Theta bands, the spectrogram plot of EEG Alpha and Theta bands and finally, the indicator of microsleep event. Here, the filtered EEG signals are the clean EEG signals which are free of eyes blinks, muscle movements and eye movements after applying the threshold of ±100 µV remover in LabVIEW block diagram. Next, Power Spectral Density (PSD) technique is applied to the clean EEG signals to obtain the EEG power spectrum or Alpha and Theta band after applying bandpass filter. In order to have better view of the occurrence of microsleep event, EEG feature extraction techniques in term of spectral centroids and standard deviation are applied to the EEG Alpha and Theta power bands and classified. Whenever the Theta band for both standard deviation and spectral centroid is larger than Alpha band, it might indicates that microsleep does take place and red LED indicator will be turned on. Otherwise, the green indicator will be turned on which indicate no occurrence of microsleep event.
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Fig. 10. Block diagram of determining Power Spectrum Density (PSD) of the EEG Alpha and Theta bands.
Fig. 11. Block diagram to calculate the STFT of the EEG Alpha and Theta bands.
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Fig. 12. Overall LabVIEW block diagram.
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EEG Power Spectrum
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Fig. 13. Overall GUI in LabVIEW.
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Analysis of Standard Deviation Value of EEG Signals
Table 2 shows the standard deviation value of the subject for Alpha and Theta bands in 3 different states which are relax state, driving car simulator and driving real car states. Theoretically, the standard deviation value for Alpha band should be higher than Theta band in relax states while in driving states (car simulator or driving real car) the Theta band should be higher. Based on the standard deviation of car simulation and driving states, microsleep event does occur for subject 4, 5 and 6 whereas there is no significant microsleep detection for the other subjects as shown in Figs. 14, 15 and 16.
Table 2. Standard Deviation value for Alpha and Theta band in 3 different cognitive states. Subject Relax Alpha 1 1.6871 2 0.5080 3 0.6542 4 0.5712 5 0.8383 6 1.2022
Theta 1.0127 0.3128 0.5120 0.3432 0.4953 1.0719
Car simulator Alpha Theta 1.6489 1.3857 1.0953 0.9814 1.2730 1.1083 0.4733 0.7783 0.9070 1.0689 1.1365 1.2140
Real car Alpha Theta 1.4929 1.2134 1.7278 1.5106 1.1620 1.0166 1.4322 1.5582 2.1810 2.4843 1.8069 1.9840
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Fig. 14. Standard Deviation in relax state.
Fig. 15. Standard Deviation in car simulator state.
Fig. 16. Standard Deviation in driving state.
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Analysis of Spectral Centroid Value of EEG Signals
Table 3 shows the spectral centroid value of the subject for Alpha and Theta bands in 3 different states which are relax state, driving car simulator and driving real car states. The spectral centroid value for Alpha band should be higher than Theta band in relax states while in driving states (car simulator or driving real car) the Theta band should be higher. Based on the spectral centroid of driving state, microsleep event does occur for subject 3, 4, 5 and 6 whereas there are no significant microsleep detection for the other subjects as shown in Figs. 17, 18 and 19. Table 3. Spectral Centroid Value for Alpha and Theta band in 3 different states. Subject Relax Alpha 1 773.74 2 828.54 3 724.30 4 680.86 5 756.97 6 800.36
Theta 651.25 748.67 627.56 626.87 731.48 776.90
Car simulator Alpha Theta 765.67 802.23 865.54 830.43 734.26 770.88 774.31 836.99 770.27 822.89 768.88 806.50
Real car Alpha 795.90 773.83 686.528 672.08 707.30 767.26
Fig. 17. Spectral Centroid in relax state.
Theta 789.36 758.63 719.38 694.50 757.37 804.55
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Fig. 18. Spectral Centroid in car simulator state.
Fig. 19. Spectral Centroid in driving state.
Table 4 represents the summary of the microsleep detection from the plotted spectrogram of the chosen subjects in relax state, driving car simulator and driving real car. Based on Table 4, only subjects 3, 4 and 5 have significant and detectable microsleep occurrence whereas the rest with no microsleep event is being detected. The time when the microsleep event might happen within of 1-h of driving as stated in Table 4 in terms of seconds. The age of the subject might play a role in the occurrence of the microsleep event and the frequency of the event to be occurred.
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Table 4. Microsleep event occurrence time in seconds. Subject Age Number of microsleep occurrence (seconds) Relax Car simulator Real car 1 22 No No No 2 24 No No No 3 24 No No No 4 25 No 1 (320) 1 (460) 5 45 No 1 (230) 1 (200) 6 50 No 2 (30, 130, 170) 3 (30, 230, 430)
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Feature Classification
In features classification, there are four training-testing ratio which are 50:50, 60:40, 70:30 and 80:20 ratios are applied to the selected EEG features which are standard deviation and spectral centroid value. The classification accuracy at each of the ratios for both feature extractions is shown in Table 5. As tabulated in Table 5, the classification accuracy percentage for standard deviation at 50:50, 60:40, 70:30 and 80:20 ratios are 58.22%, 62.56%, 72.78% and 82.83% respectively while spectral centroid with accuracy percentage of 55.23%, 60.15%, 69.25% and 77.65% respectively. The highest classification rate is obtained at 80:20 training-testing ratios in both cases. Thus, it can be concluded that 80:20 training-testing ratio is the best among these four ratios where the accuracy to classify microsleep event using standard deviation is higher than spectral centroid. The selected EEG features in term of SD and SC is classified separately in order to figure the out the best features that might indicate the presence of microsleep event. Since only 2 EEG features are selected and classified with various type of training-testing ratio with higher accuracy rate obtained at 80:20 training-testing ratios, it is not necessary to calculate the sensitivity or specificity test for the selected EEG features. Table 5. KNN classification results. Training-testing ratios Accuracy standard deviation Spectral centroid 50:50 58.22 55.23 60:40 62.56 60.15 70:30 72.78 69.25 80:20 82.83 77.65
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Spectrogram Analysis
Beside the EEG feature extraction and classification to detect the changes in EEG Alpha and Theta bands for the occurrence of microsleep event, Spectrogram or ShortTime Fourier Transform technique is applied to EEG Power Spectrum to determine the time of the occurrence of microsleep event as stated in Table 4. In Spectrogram plot, the occurrence of microsleep event is indicated by the presence of red spot in EEG Theta band spectrogram as shown in Fig. 20. Based on the figure, it can be said that the microsleep event occurred as earlier as 30 s and within 200 to 400 s after real driving or simulator driving. The occurrence can be repeated from time to time. The number of microsleep occurrence also might depend of the age of the subjects.
Fig. 20. EEG Theta spectrogram of the subject.
4 Conclusion The offline microsleep detection system is successfully implemented to detect microsleep event of the vehicle driver based on EEG signals. The LabVIEW front panel or GUI and Block Diagram are successfully constructed to analyze the EEG signals where power spectrum of Alpha and Theta band of EEG signal is extracted for microsleep indication. The EEG feature in term of Standard Deviation of Alpha and Theta power spectrum is the best feature to detect the presence of microsleep event based on higher classification rate accuracy compared to other selected EEG features, Spectral Centroid. Based on the research findings, the subject is in relaxed condition when Alpha band is higher than Theta band. Meanwhile, the subject is felling sleepy or drowsy whenever the Theta band is more dominate than Alpha band. Hence, EEG spectrogram is finally plotted to determine the highest probability of microsleep spot to occur and when it might occurs. The future work will include analysis of micro sleep from large sample of EEG database, to classify other EEG features and to classify others EEG features in order to enhance the online microsleep detection system before implementing online or real-time system.
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Acknowledgement. The first author would like to thank his undergraduate students and research team members for their great support in this research. Special thanks also go to Faculty of Electrical & Electronics Engineering and Universiti Malaysia Pahang for providing financial support through research grant, RDU180396.
References 1. Tang, R.: Death rates on Malaysian roads is 3rd highest globally, more than China and India. Says (2017) 2. Putra, A.E., et al.: EEG-based microsleep detector using microcontroller (2016) 3. Poudel, G.R., Innes, C.R., Bones, P.J., Watts, R., Jones, R.D.: Losing the struggle to stay awake: divergent thalamic and cortical activity during microsleeps. Hum. Brain Mapp. 35 (1), 257–269 (2014) 4. Knopp, S.J.: A multi-modal device for application in microsleep detection, May 2014 5. Ben Dkhil, M., Wali, A., Alimi, A.M.: Drowsy driver detection by EEG analysis using Fast Fourier Transform. In: International Conference on Intelligent Systems Design and Applications, ISDA 2016, pp. 313–318 (2016) 6. Van Hal, B., Rhodes, S., Dunne, B., Bossemeyer, B.: Low-cost EEG-based sleep detection. In: 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014, pp. 4571–4574 (2014) 7. Hassib, M.: Mental task classification using single-electrode brain computer interfaces (2012) 8. Sulaiman, N., Taib, M.N., Lias, S., Murat, Z.H., Aris, S.A.M., Hamid, N.H.A.: Novel methods for stress features identification using EEG signals. Int. J. Simul. Syst. Sci. Technol. 12(1), 27–33 (2011) 9. Pragatheeswaran, K., Mahashruthi, S.: Detection of driver’s drowsiness using EEG system 3 (22), 26–30 (2017) 10. Dumitrescu, C., Costea, I.M., Banica, C.K., Potlog, S.: LabVIEW brain computer interface for EEG analysis during sleep stages, pp. 285–288 (2015) 11. Sulaiman, N., Armiza, S., Aris, S.A.M., Hayatee, N.: EEG-based stress features using spectral centroids technique and k-nearest neighbor classifier. In: UkSim 13th International Conference on Computer Modelling and Simulation, pp. 69–74 (2011) 12. Baba, T.: Time-frequency analysis using short time Fourier transform. Open Acoust. J. 5, 32–38 (2012) 13. Mustafa, M., Taib, M.N., Lias, S., Murat, Z.H., Sulaiman, N.: EEG spectrogram classification employing ANN for IQ application. In: The International Conference on Technological Advances in Electrical, Electronics and Computer Engineering, pp. 199–203 (2013) 14. Rahman, T., Ghosh, A.K., Shuvo, M.H., Rahman, M.: Mental stress recognition using Knearest neighbor (KNN) classifier on EEG signals (2018) 15. Paul, A., Boyle Ng, L., Tippin, J., Rizzo, M.: Variability of driving performance during microsleeps (2005)
Vision Based Automated Badminton Action Recognition Using the New Local Convolutional Neural Network Extractor Nur Azmina Rahmad1, Muhammad Amir As’ari2(&), Mohamad Fauzi Ibrahim3, Nur Anis Jasmin Sufri1, and Keerthana Rangasamy1 1
School of Biomedical Engineering and Health Sciences, Faculty of Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia 2 Sport Innovation and Technology Center (SITC), Institute of Human Centered Engineering (IHCE), Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia [email protected] 3 Institut Sukan Negara, Kompleks Sukan Negara, Bukit Jalil, 57000 Kuala Lumpur, Malaysia
Abstract. Performance analysis is essential in sports practice where the athlete is evaluated to improve their performance. Due to the rapid growth of science and technology, research on automated recognition of sports actions has become ubiquitous. The implementation of automated action recognition is an effort to overcome the manual action recognition in sport performance analysis. In this study, we developed a model for automated badminton action recognition from the computer vision data inputs using the deep learning pre-trained AlexNet Convolutional Neural Network (CNN) for features extraction and classify the features using supervised machine learning method which is linear SupportVector Machine (SVM). The data inputs consist of badminton match images of two classes: hit and non-hit action. Before pre-trained AlexNet CNN was directly extracting the features, we introduced the new local CNN extractor in recognition pipeline. The results show that the classification accuracy with this new local CNN method achieved 98.7%. In conclusion, this new local CNN extractor can contribute to the improvement of the performance accuracy of the classification task. Keywords: Action recognition Network Badminton
Deep learning Convolutional Neural
1 Introduction Nowadays, sport performance analysis is not something new in the sport field. It has been widely used by coaches and analyst experts to evaluate and improve the performance of athletes during the competition, sport event or coaching session. Due to a massive access to technology and computer science, the analysis can be done easily © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 290–298, 2020. https://doi.org/10.1007/978-981-15-3270-2_30
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using the vision based modality on the established performance analysis software such as Dartfish, Nacsport, Performasports and LongoMatch. However, the major issue of the current performance analysis is manual action annotation that need to be done by analyst is unpractical, time consuming and susceptible to human error. Therefore, studies to develop an automated human action recognition (HAR) in sports have been proposed by many researchers by using either conventional machine learning or deep learning approach. The establishment of automated action recognition is beneficial for coaches and analyst experts to make their analysis more effective and accurate [1]. In HAR task, there are several techniques introduced by previous researchers. The first one is handcrafted features extraction and classification using conventional machine learning technique such as decision tree, support vector machine, hidden markov models and naïve Bayes [2, 3]. Secondly, the most promising and popular technique nowadays is deep learning technique [4]. In deep learning, Convolutional Neural Network (CNN) is the common approach that has been used for HAR from the video frame that represent human action [5–7]. This is due to the fact that CNN is excellent in image recognition task which is almost similar to video frame recognition task in video based recognition problem. However, the conventional CNN that is applied directly and globally to the whole image frame pixels is not susceptible to the influence of background pixels which might fail the recognition process especially when the region of interest in the input video frame is too small. Thus, the focus of this paper is to discuss the proposed automated badminton action recognition (between hit and non-hit action) from the broadcast video of badminton match using new proposed local CNN extractor and linear SVM classifier which outperform the conventional global CNN approach.
2 Related Works Human action recognition (HAR) is a task of formulating an automated algorithm for recognizing or classifying human actions which in general can be divided into two categories: (1) HAR based on wearable sensor; (2) HAR based on vision sensor. HAR involves in many applications such as video surveillance [8], human-computer interaction, virtual reality systems, human monitoring [9–12] and sport analytic systems [13, 14]. Wearable sensor refers to the method of positioning the sensor such as inertial sensor and accelerometer [15–17] at human body that produce one-dimensional signals related to the body movement. Meanwhile, vision sensor is the approach that focused on the special camera setup or Kinect [18] to capture the information in form of video sequences. HAR is a challenging task for both modalities in which sensor based faces problems such as lack of information as it depends on one-dimensional signals and less practical because it bounded on the multiple sensors system for more accurate recognition. As for vision based, the challenges are occlusion, illumination and view point variations and background differences [19] on the video data inputs. In HAR based on vision sensor task, there are several techniques introduced by previous researchers. The first one is handcrafted features extraction and classification using conventional machine learning technique such as decision tree, support vector machine, hidden markov models and naïve Bayes [2, 3]. Previously, most of the works
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were done using the handcrafted machine learning approach such as works in [2, 20– 22]. Secondly, the most promising and popular technique nowadays is deep learning technique [4, 23]. The use of deep learning methods in recognizing human actions is not new in computer vision field, as many researches have been done in this area. Due to the availability of enormous dataset, deep learning technique has becoming a bombing interest in action recognition especially using CNN method. The current machine learning technique is relying on the heuristic handcrafted features extraction which is bounded to the human domain knowledge. In brief, features extraction need to be done manually before classifiers classify the shallow learned features [24]. Deep learning technique is subtype of machine learning. It is an improved technique that eliminates the manual features extraction in machine learning pipeline. The features are being learned automatically from the low-level features at the first layer until high-level features at the deepest layer to perform classification task directly from the input data. Figures 1 and 2 illustrate the machine learning and deep learning pipeline. There are various methods in deep learning such as deep stacking network (DSN), deep belief network (DBN), recurrent neural network (RNN), long-short term memory (LSTM) and frequently used in many research is CNN. Input data of sensor based or vision based
Features extraction
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Fig. 1. Machine learning pipeline
Input data of sensor based or vision based
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Fig. 2. Deep learning pipeline
As a deep learning network, CNN comprises of input layer, hundreds of hidden layers and output layer. The features were attained from the convolutional process between filters and input data. Next, the activated features were transmitted from one layer to the next layer before being classified at the final fully connected layers. There are mainly three methods to use CNN which depending on the type of application – training from scratch, transfer learning of pre-trained CNN or feature extraction. Training deep learning from scratch required a huge number of labelled dataset and longer training period. This approach however is suitable to be used for a new application or application with many output classes. Second method is transfer learning approach which researchers mostly use. This method involves fine-tuning the pretrained model such as AlexNet [25], GoogleNet, SqueezeNet, ResNet and VggNet [7] with own labelled dataset. After tuning the model with own dataset, a new classification task can be performed. The advantage of this method compared to training from scratch method is that it required less number of dataset. Hence, the training time is faster.
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Lastly, it can also be used as more specialized approach which is feature extractor. Since features were learned in each layer, features can be extracted to be classified by other machine learning model such as SVM. Some researchers reviewed sport action recognition based on deep learning methods and generally, most are focusing on football and basketball [26]. Due to the rapid development of technology nowadays, most of the researchers are utilizing the video-content analysis approach for sport action recognition. For example, work in [27] used video dataset to classify five hockey actions using pre-trained CNN method and [5] classify low and high resolution video dataset using CNN method. Meanwhile, Baccouche et al. [28] used subtype of Recurrent Neural Networks (RNN) which is LSTM to recognize soccer actions. In deep learning, the method that is widely used is CNN. However, in recognizing different type of actions with excellent performance, researchers have proposed the method of fusing few deep learning methods. For example, work in [29] used video dataset to recognize sport actions using CNN and bidirectional Long Short Term Memory (LSTM) deep learning method. As in this paper, we utilized the pre-trained AlexNet CNN model as a features extractor and SVM as a classifier to classify hit and non-hit actions from badminton broadcast videos. We also proposed our new local CNN extractor method in deep learning pipeline to improve the performance accuracy of the deep learning model in classifying the badminton actions.
3 Methodology In this section, the proposed method and the experimental framework are discussed in detail. The experiment was conducted on our own constructed dataset obtained from five broadcasted badminton match videos. There are two classes of dataset which is hit and non-hit action of total 2990 images compressed to 227*227 where 60% from the total images sample are used for training, 20% for testing and another 20% for validation. The details of dataset used in this experiment are as follow (Table 1). Table 1. Details of dataset Class Hit Non-hit Total
Number of training sample 897 897 1794
Number of testing sample 299 299 598
Number of validation sample 299 299 598
Figure 3 shows the methodology of the experiment. Unlike the normal deep learning pipeline that train the image data globally (global method), we introduce the local CNN method before the feature extraction by deep learning. The purpose of introducing this new method in deep learning pipeline is to investigate whether the preprocessing can contribute to the performance of the deep learning approach. The term
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‘new local CNN’ refers to the new local technique introduced into the transfer learning pipeline. Previously, studies used global CNN technique that directly processes the whole image frame into feature extraction by transfer learning model. However, in this study, we introduced the ‘new local CNN’ technique before feature extraction by transfer learning model. To obtained the localize data information, we cut the globalize image into two equal localize images (upper and lower part). For a clear explanation about the methodology, refer Fig. 4.
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Fig. 3. The block diagram of the methodology
At the beginning of this study, each localize images were trained separately using the pre-trained AlexNet CNN to obtain the features for upper localize and lower localize images. The training took place on Nvidia GeForce GT 740 with computing capability 3.0 using Matlab 2018b. Next, both features from upper and lower localize images that were extracted at fc8 layer were classified using SVM classifier to predict the action class either hit or non-hit action. The performance of the proposed method was analysed and illustrated in form of confusion matrix and accuracy table. The experiment was repeated using normal globalize CNN feature extractor to compare and observe the difference on their performance accuracy.
4 Results and Discussion Table 2 shows the accuracy table for classification task of both global and local CNN feature extractor trained using AlexNet model and classified using SVM classifier. Interestingly, for our proposed local CNN method, the performance accuracy was found higher compared to the traditional global CNN method. In our view, the result empahizes the validity of our method. Generally, CNN process the whole raw image frame pixels to extract the features. However, with our proposed method, instead of extensively process the whole image frame, the global image frame was divided into two equal local parts. We believe that the local method is more accurate because it carries more informations since each local part containing smaller background area or pixels as compare to processing whole image frame globally. Thus, the local CNN is susceptible to the influence of background pixels. Figures 5 and 6 show the confusion matrix of global and local CNN feature extractor. From Fig. 5, 5 hit actions were falsely classified as non-hit action and 8 nonhit actions were falsely classified as hit action and it make a total of 13 images were falsely classified (2.2% of misclassification). As in Fig. 6, from a total of 299 hit actions, 6 were falsely classified as non-hit and from 299 non-hit actions, 2 were falsely classified as hit. A total of falsely classified actions are only 8 images which make the accuracy is higher compared to the previous one (1.3% of misclassification).
Vision Based Automated Badminton Action Recognition AlexNet feature extractor
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Fig. 4. The illustration of experimental setup Table 2. Accuracy table
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5 Conclusion As a conclusion, we found out that the local CNN extractor introduced in the deep learning pipeline as a part of pre-processing can improve the performance action recognition. Eventhough there are a lot of study have been done by other researchers in action recognition using deep learning approach, a lot of improvement is still needed. Hence, we believe that our proposed method can be used to enhance the performance of action recognition. In future, using our proposed method, we will study more on classifying the specific actions in badminton. Acknowledgement. The authors would like to express their gratitude to Universiti Teknologi Malaysia (UTM) and the Minister of Education (MOE), Malaysia for supporting this research work under Zamalah UTM and FRGS Research Grant No. R.J130000.7851.5F108.
References 1. Cust, E.E., et al.: Machine and deep learning for sport-specific movement recognition: a systematic review of model development and performance. J. Sports Sci. 37(5), 568–600 (2019) 2. Zerrouki, N., et al.: Vision-based human action classification using adaptive boosting algorithm. IEEE Sens. J. 18(12), 5115–5121 (2018) 3. Tejero-de-Pablos, A., et al.: Human action recognition-based video summarization for RGBD personal sports video. In: 2016 IEEE International Conference on Multimedia and Expo (ICME) (2016)
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Investigation of Different Time-Series Segmented Windows from Inertial Sensor for Field Hockey Activity Recognition Norazman Shahar1, Nurul Fathiah Ghazali1, Muhammad Amir As’ari1,2(&), Tian Swee Tan1, and Mohamad Fauzi Ibrahim3 1
School of Biomedical and Health Sciences, Faculty of Engineering, Universiti Teknologi Malaysia (UTM), Johor Bahru, Malaysia [email protected] 2 Sports Innovation and Technology Center (SITC), Institute of Human Centered Engineering (IHCE), Universiti Teknologi Malaysia (UTM), Johor Bahru, Malaysia 3 Institut Sukan Negara, Kompleks Sukan Negara, Bukit Jalil, 57000 Kuala Lumpur, Malaysia
Abstract. Sport activity recognition has become one of the primary sport performance analysis contributions as it offers a notational data for tactical analysis and planning. In developing of activity recognition algorithm, searching for the best window segmentation size within time-series data is one of the parameters that contribute to the performance of algorithm in term of the accuracy rate. Yet, previous studies on activity recognition have implemented a different fixed size of window in segmenting the specific activities and the performance of activity recognition algorithm along with the changes of window size is still uncertain. Thus, this study is investigating the performance of field hockey activity recognition algorithm based on inertial sensor time-series data with different window segmentation size. The study was conducted on 11 subjects who worn the inertial sensors on their chest and waist while performing the six common field hockey activities which are passing, drive, drag flick, dribbling, receiving and tackles. The performance of each size of windows were observed and evaluated by using Cubic support vector machine (SVM). Among the different window sizes studied, this study found 1.5 s and 2.0 s are among the top in producing high accuracy rate for recognizing the field hockey activity that represent the movement from chest and waist with 89.6% and 91.4% accuracy respectively. Keywords: Activity recognition Support vector machine Field hockey sport
1 Introduction 1.1
Background of Study
Reliability on notational data and coaching feedback are recognized as one of the major influences and impacts toward the probability of game winning and losing. It was © Springer Nature Singapore Pte Ltd. 2020 M. H. A. Hassan et al. (Eds.): MoHE 2019, LNBE, pp. 299–310, 2020. https://doi.org/10.1007/978-981-15-3270-2_31
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studied that, having a notational data of collection successful and unsuccessful of sport activity did provide a higher probability of winning [1]. Due to the important of feedback within the coaching process, the data collection is practiced through observational method using video-based technology [2]. Issues such as the necessity of experts and replayback video to annotate sport activity are rose during the analyzing performance process [3]. One of the promising solutions to overcome the issues, known as automated activity recognition algorithm. The aim of such system is to allow coach and notational analyst to have reliable and accurate information without the need of expertise and preventing the biasing issue. Activity recognition based study has covered a wide range of human fields of area such as assistive living [4, 5] and monitoring of athletic activities [6–9]. The importance of activity recognition is to provide information of what people’s doing for example to provide a monitoring of elderly people. However, in sports, activity recognition system is useful to (1) understand which areas need to be focused [10], (2) identify the strengths and weaknesses of athletes [10, 11], (3) identify the early cues of injury [11] and (4) create a well-planning strategy [10]. Among available assisted living systems, inertial sensor is one of the example modalities incorporated with sensing and data processing techniques [12] to provide coaching assistance about athlete’s daily training and in-game performance. Inertial sensor has been widely used to provide information about human’s actions and behavior. Commercialized product in field hockey performance and study, inertial readings such as accelerometer, gyroscope and magnetometer incorporated with global positioning position (GPS) for positional tracking such as total distance, sprinting and running. As inertial sensors are small in size, portable, low cost production and mainly the flexibility of gathering signals and processing with machine learning techniques for classification are the main reason why this study utilized inertial sensors for activity recognition in field hockey. The activity information definitely could be implemented as an assisted system in sports study to react and adapt to the circumstance of the user purposely to improve sport performance among athletes. The objective of this paper is to identify the best segmented window size approach for field hockey activities (passing, drive, drag flick, dribbling, receiving and tackles) using signals from accelerometer and gyroscope readings from chest and waist mounted. The proposed segmented windows in this study can detect dynamic and transitional activity signals with varying duration. The window size is successfully studied for continuous evaluation in a control environment in which field hockey activities is performed orderly. As a result, a more effective window size can be selected for segmentation to achieve more accurate classification. The rest of the paper is organized as follows. Relevant and current available studies that used signal segmentation techniques for sport activity recognition systems are presented in Sect. 1.2. Follow with data collection, segmenting signals features extraction for activity recognition are described in Sect. 2. Section 3 presents the results and discussion as well as conclusions presented in Sect. 4. 1.2
Related Work
Signal segmentation is the early crucial process in the sensor-based activity recognition system whereby it divides a large signal into smaller segments for next feature
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extraction and classification process. The importance of time-series segmented windows in this study is to find appropriate window period as each activity has different window period. Generally, signal segmentation can be classified into three techniques, activity-defined windows, event-defined windows and sliding windows [13, 14]. Segmentation of activity-defined technique allow the data stream to be partitioned as the system detect of activity changes [13]. This technique is very limited in real application due to only applicable in controlled setting such as laboratory and under the expert supervision [13]. For event-defined windows, the specific events from the data streams will be identified for segmentation process. This approach mainly used in gait analysis and since the events may not be uniformly distributed in time, the size of corresponding windows is not fixed. The event-defined technique divides the data by locating specific event. In this method, the window size is not fixed as the time is not uniformly distributed [13, 14]. The sliding window approach is widely applied for segmentation technique in activity recognition which is presented in work by Banos et al. [13] mainly are walking, sitting, jogging and running. Those activities that were presented in work [13] are the common human activity daily living. However, in sports activity recognition, it is still unclear due to activity performed is unlikely to human activity daily living and most of the time, the duration too short. Sliding window technique offers a simple and lack of preprocessing for windowing approach in realtime applications which is motivation to be investigated for field hockey activity recognition in this study. Table 1 show several previous works studied on sport activity recognition using window sliding method in recognizing sport activity recognition.
Table 1. Sport activity recognition using sliding window approach Previous study Wang et al. [15]
Sport category Badminton
Kelly et al. [16] Hardegger et al. [17] Nguyen et al. [18] Rawashdeh et al. [19]
Rugby Ice hockey Basketball Baseball and volleyball
Sport activity Strokes: forehand and backhand serve forehand and backhand clear, forehand and backhand rushing, forehand and backhand chop, forehand and backhand lob, forehand and backhand push, forehand and backhand hook on the corner Non stroke: walking and pick up a ball, forehand and backhand cross footwork Running, jumping, falling, tackling, rucks and mauls Skating, power strokes, breaking, turns, jumps and curves Walking, running, jogging, pivot, shooting from different locations, layupshot and sprinting Sport activity: Baseball and volleyball throw, baseball and volley ball serve Rehab exercise: Flexion, extension and scapular punch
Window size 2.5 s
2.56 s 0.6 s, 1.0 s 3.2 s 1.0 s
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2 Methodology This section discussed the proposed method for searching best window size for activity recognition in field hockey. Figure 1 shows a general work flow that used in this study.
Data acquisition and collection
Set window period to 0.5 second
Segmenting and sliding of fixed window size
Extraction of fixed features from signal
Window period + 0.5 second
Data train and testing
If window period ≤ 3 seconds
Accuracy comparison
Fig. 1. A flowchart of proposed method for activity recognition in field hockey sport
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Data Acquisition and Collection
In data collection, 11 field hockey players were asked to perform six types of field hockey activity which are passing, drive, drag flick, dribbling, receiving and tackling while wearing multiple inertial sensors. Each general activity is performed into several specific activities as shown in Table 2. Each activity is repeated three times. Table 2. List of field hockey activities General field hockey activity Specific field hockey activity Passing Push pass Slap Hit Drive Drive Drive with moving ball Drag flick Drag flick Dribbling Tease the cone Forehand drag Body switch Indian dribble Lead and pull back Receiving Receiving front Receiving right Receiving left Tackling Block tackle Jab tackle Lunge tackle Reverse tackle Interception open Interception reverse Closing down open stick Closing down reverse stick
Fig. 2. Physilog® 4 Silver inertial sensors and sensor placement at chest and waist
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Two Physilog® 4 Silver inertial sensors Fig. 2(a) were worn on chest and waist a Fig. 2(b) and (c) respectively. The attachment of inertial sensors to body of player are using Velcro strap. Physilog® 4 Silver inertial sensor has the following attributes which are time, acceleration (tri-axial accelerometer), angular rotation (tri-axial gyroscope), (tri-axial magnetometer) and (barometer). Mostly of the existing study, there are two typical types of sensors used to represent movement detection, which are accelerometer sensor only or fusion of accelerometer and gyroscope sensor. In this study, the signal of accelerometer and gyroscope were considered. The sampling frequency used for field hockey activity recognition was set to 200 Hz. Activity annotation is very crucial at the initial stage. Unlike recording or camera sensor, inertial sensor is totally human activity recognition based on signal. Each movement or activity performed by athletes is recognized by the changes of inertial sensor signal. Therefore, during data collection process, recording during performance was taken in order to synchronize with inertial signal and accurately for activity annotation as shown. Note that, three times tapping on each inertial sensor is required to indicate the point of synchronization. Video recording and inertial signal were synchronized using Elan software. For labelling process, the field hockey movements are labelled by using software known as Physilog Researcher’s Toolkit from Gait up. 2.2
Segmenting and Sliding of Fixed Window Size
Window segmentation is next the processing signal which is very important as proven few works [13, 20] which is contributing to impact on activity recognition system. Equation (1) illustrates the number of samples is segmented within window period. Table 3. List of field hockey activities Field hockey activity Push pass Slap Hitting Drive Drive with moving ball Drag flick Receiving front Receiving right Receiving left Block tackle Jab tackle Lunge tackle Reverse tackle Interception open Interception reverse Closing down open stick Closing down reverse stick
Average segmentation size (s) 0.53 0.63 0.63 0.57 1.87 0.90 1.80 2.00 2.00 0.63 0.64 0.70 0.85 1.30 1.16 1.60 1.00
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window periodsðsÞ ¼
window size Sampling frequency ðHzÞ
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ð1Þ
Table 3 shows the average segmentation size of performing field hockey activities. From the Table 3, push pass activity has the short period that was performed by subjects and as a reference point of for window size. Since the average window size for all activity in field hockey is less than 3 s, the window sizes of 0.5 s, 1.0 s, 1.5 s, 2.0 s, 2.5 s and 3.0 s were evaluated in this study. The duration of dribbling was not included as the dribbling activities were performed repeatedly. During the segmentation process, the labelled signal was segmented using a fixed-width sliding windows with 50% overlap. In this study, window overlapping is necessary and intended to handle transition more accurately as sports movements are extremely vigorous and physically rugged. 2.3
Extraction of Fixed Features from Signal
Statistical features such as mean, standard deviation, maximum and minimum values were extracted from each inertial sensor and used to create a feature vector. The following equations represent time-domain features: Mean equation l¼
1 Xn a i¼1 i n
ð2Þ
Standard deviation equation rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 1 Xn r¼ ja lj2 i¼1 i n1
ð3Þ
amin ¼ mini2½n ai ; ½n ¼ f1; 2; 3; . . .; ng:
ð4Þ
Minimum peak equation
Maximum peak equation amax ¼ maxi2½n ai ; ½n ¼ f1; 2; 3; . . .; ng
ð5Þ
The values of mean, standard deviation, minimum and maximum were extracted from each inertial sensor. There are two inertial sensors were studied to recognize field hockey movements. Therefore, 6 4 = 24 features were used as an input for classification purpose for each inertial sensor. In this study, supervised of Cubic Support Vector Machine was used to classify to recognize field hockey activities. 10-fold cross validation method was set for Cubic SVM classifier to classify the activity. The performance of Cubic SVM for each activity is evaluated from the confusion matrix. The Cubic SVM classifier in toolbox of Matlab 2019a for this study has the following configuration, value of 1 for box constraint level and one vs one multiclass method.
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The box constraint level value of 1 is preferred as it to maintain the number of support vectors along with less computational time for data training. One vs one multiclass method is implemented to allow the Cubic SVM learns to differentiate one class from the other class.
3 Result and Discussion The results are discussed in terms of the Cubic SVM performance upon the investigation of different window periods which are 0.5 s, 1 s, 1.5 s, 2 s, 2.5 s, and 3 s. Figure 3 shows the overall Cubic SVM accuracy obtained from the recognition of six field hockey activities by using chest and waist sensor mounted. In Fig. 3, notice that the difference in window size is empirically offering a drastic impact on Cubic SVM classifier performance. From 1 s up to 1.5 s, both sensors mounted showed an increasing of Cubic SVM performance However, at 1.5 s, performance of Cubic SVM at chest achieved the best accuracy with 89.6% and extremely dropped to 74.1% at 3.0 s. But, performance of Cubic SVM at waist has reached the best overall performance at 2.0 s with 91.4% and found to be declined slightly till 3.0 s with 88.0%. As segmented window (window size) are getting longer, information within a segmented window were mixed and distorted with different activity which is could lead to the misinterpretation and misclassify during modelling with Cubic SVM as the main reason of accuracy declination.
Fig. 3. Performance of Cubic SVM with varies of different window sizes.
Passing
Passing Drive Drag flick Dribbling Receiving Tackling
Passing Drive Drag flick Dribbling Receiving Tackling
Passing Drive Drag flick Dribbling Receiving Tackling
Actual
2.0 s 86%