Journal of Exercise and Health Science

Postural Balance for Selection of Martial Artists Using Machine Learning Techniques

Document Type : Original Article

Authors

1 Alborz University of Medical Sciences, Karaj, Iran

2 BSc Graduate in Biomedical Engineering. MSc Graduate in Electrical Engineering, Amirkabir University of Technology Tehran, Iran

3 Former Biomedical Engineering Expert, Department of Medical Equipment, ABZUMS, Karaj, Iran.

4 Medical Lab Sciences Technologist, Head of the Department of Medical Equipment, ABZUMS, Karaj, Iran.

5 Department of Biomedical Engineering, Islamic Azad University (IAU), Science and Research Branch, Tehran, Iran

10.22089/jehs.2022.6782.1000
Abstract
Objectives: The purpose of this study was to classify participants, according to balance test scores, and to detect martial art athletes.
Design: Measures of static and dynamic balance indices were obtained from 4 tests.
Setting: This research took place at a secondary school in Iran.
Participants: Fifty healthy volunteers participated in this experiment.
Main outcome measures: Due to differences in power and different pressures applied on joints and muscles, athletes in different sports and also non-athletes may have different grades in balance tests. There isn’t enough information on specific or non-specific balance in sports.
Results: Balance test scores were used for inputs of classifiers where the applied methods included the support vector machine, k-nearest neighbors algorithm, and artificial neural network. Only by the result of 4 tests, detection accuracy of 90.5% was achieved.
Conclusion: Balance indices are good features for detection of martial art athletes. This may also be useful for talent identification in martial arts.

Keywords

Journal of Exercise and Health Science
Volume 2, Issue 1
January 2022
Pages 1-12

Article View 10,792
PDF Download 7,531

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