@article { author = {Manshadi, Muhammad and Ranjbar, Ehsan and Ghasab Sedehi, Reyhaneh and Hassani, Navid and Jafarnia Dabanloo, Nader}, title = {Postural Balance for Selection of Martial Artists Using Machine Learning Techniques}, journal = {Journal of Exercise and Health Science}, volume = {2}, number = {1}, pages = {1-12}, year = {2022}, publisher = {Sport Sciences Research Institute of Iran}, issn = {2783-1647}, eissn = {2783-1647}, doi = {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 = {Artificial neural network,Balance,Classification,K-nearest neighbors,Support vector machine}, url = {https://jehs.ssrc.ac.ir/article_3576.html}, eprint = {https://jehs.ssrc.ac.ir/article_3576_7ad2f508a6cac35b85f031e4dbca33a1.pdf} }