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

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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Publication Details

Published
2024-12-11
DOI
https://doi.org/10.1145/3726122.3726207
Citations
1
Primary Topic
Muscle activation and electromyography studies
Type
article
Field-Weighted Citation Impact
0.18
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article

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

Gulrukh Sherboboyeva, Kudratjon Zohirov, Sardor Boykobilov, Mirjakhon Temirov et al.
1 citations
Muscle activation and electromyography studies
0.18
article

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

Gulrukh Sherboboyeva, Kudratjon Zohirov, Sardor Boykobilov, Mirjakhon Temirov, Mamadiyor Sattorov
article en
1 citations

Abstract

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.

Tashkent University of Information Technology (UZ), Tashkent State University of Economics (UZ)
Gender equality
Openalex Percentile: Top 48%
Muscle activation and electromyography studies
0.18
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