Document Type : Original Article

Authors

• Muhammad Manshadi ¹
• Ehsan Ranjbar ²
• Reyhaneh Ghasab Sedehi ³
• Navid Hassani ⁴
• Nader Jafarnia Dabanloo ⁵

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

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

• Artificial neural network
• Balance
• Classification
• K-nearest neighbors
• Support vector machine