%0 Journal Article %T Postural Balance for Selection of Martial Artists Using Machine Learning Techniques %J Journal of Exercise and Health Science %I Sport Sciences Research Institute of Iran %Z 2783-1647 %A Manshadi, Muhammad %A Ranjbar, Ehsan %A Ghasab Sedehi, Reyhaneh %A Hassani, Navid %A Jafarnia Dabanloo, Nader %D 2022 %\ 01/01/2022 %V 2 %N 1 %P 1-12 %! Postural Balance for Selection of Martial Artists Using Machine Learning Techniques %K Artificial neural network %K Balance %K Classification %K K-nearest neighbors %K Support vector machine %R 10.22089/jehs.2022.6782.1000 %X 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. %U https://jehs.ssrc.ac.ir/article_3576_7ad2f508a6cac35b85f031e4dbca33a1.pdf