Postural Balance for Selection of Martial Artists Using Machine Learning Techniques

Publish Year: 1400
نوع سند: مقاله ژورنالی
زبان: English
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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 ۴ 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 ۴ tests, detection accuracy of ۹۰.۵% 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.


Muhammad Manshadi

Alborz University of Medical Sciences, Karaj, Iran

Ehsan Ranjbar

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

Reyhaneh Ghasab Sedehi

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

Navid Hassani

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

Nader Jafarnia Dabanloo

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