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An EMG Signal Based Approach for Assessing the Physical Condition of Athletes in Wrestling

Kudratjon ZohirovDepartment of Computer Systems, Karshi Branch of the Tashkent University of Information Technologies named after Muhammad Al Khwarizmi, Karshi, UzbekistanRashid NasimovDepartment of Artificial Intelligence, Tashkent State University of Economics, Tashkent, UzbekistanSardor BoykobilovDepartment of Computer Systems, Karshi Branch of the Tashkent University of Information Technologies named after Muhammad Al Khwarizmi, Karshi, UzbekistanGulrukh SherboboyevaDepartment of optical communication systems and network security, Karshi Branch of the Tashkent University of Information Technologies named after Muhammad Al Khwarizmi, Karshi, UzbekistanMirjakhon TemirovDepartment of information technology software, Karshi Branch of the Tashkent University of Information Technologies named after Muhammad Al Khwarizmi, Karshi, UzbekistanMamadiyor SattorovDepartment of information technology software, Karshi Branch of the Tashkent University of Information Technologies named after Muhammad Al Khwarizmi, Karshi, Uzbekistan
2024en
ABI

Аннотация

This scientific research presents the work conducted based on EMG signals for assessing and monitoring the physical condition of athletes in wrestling. In this study, 8 physical exercises commonly used in wrestling and 2 technical techniques were selected as the main criteria for assessing the physical condition of the athletes. During the execution of these exercises and techniques, EMG signal values were recorded based on sensors placed at the most potential points of the athletes' bodies. In order to classify physical qualities, 5 classification algorithms were used, when the athletes’ activities being classified into 10 classes based on EMG signal values. During the classification process, the model with the highest accuracy and the smallest reaction time was selected. Based on the classified data, it is possible to make a conclusion that how well they are performing their daily training exercises and their activity level and performance.

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Показатели — AkademScholar · Скоро