Analysis of Y-Balance Test Data Used in Sports Sciences with Machine Learning Methods
Yazarlar (3)
Süheda Çilek Karabük Üniversitesi
Doç. Dr. Caner ÖZCAN Karabük Üniversitesi, Türkiye
Dr. Öğr. Üyesi Bahar Ateş Türkiye
| Makale Türü | Özgün Makale (Diğer hakemli uluslarası dergilerde yayınlanan tam makale) | ||
| Dergi Adı | European Journal of Engineering and Natural Sciences | ||
| Dergi ISSN | 2458-8156 | ||
| Dergi Tarandığı Indeksler | EBSCO, ProQuest One Academic, Google Scholar | ||
| Makale Dili | İngilizce | Basım Tarihi | 01-2023 |
| Cilt / Sayı / Sayfa | – / 1 / – | DOI | – |
| Makale Linki | https://cnrpublishing.com/index.php/ejens/index | ||
| UAK Araştırma Alanları |
Makine Öğrenmesi
Yapay Zeka
Görüntü İşleme
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| Özet |
| Abstract The Y-Balance Test (YBT) is a popular method used to evaluate the dynamic balance and functional mobility of athletes. However, it is crucial to perform the test correctly to obtain accurate results. For precise measurement of YBT data, a separate measurement should be conducted for each individual, and the test grid and equipment must be set up correctly. Clear instructions and a standardized protocol must be followed to avoid misleading results, which can lead to incorrect information being used to design training programs to improve athletes' performance and reduce injury risks. To address this challenge, a study was conducted using supervised learning methods to explore YBT data, perform preprocessing steps, and conduct a comparative analysis of different machine learning models' performance in predicting YBT data. The study predicted YBT values, which require individual measurements … |
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