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All Journal Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Audrian, Nathaniel
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Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Journal : journal of information technology and computer science

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Volitional Fatigue Monitoring System Using Random Forest With Root Mean Square and Integrated Electromyogram Feature Audrian, Nathaniel; Widasari, Edita Rosana
Journal of Information Technology and Computer Science Vol. 10 No. 1: April 2025
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.2025101924

Abstract

Athletes often hire personal trainers (PTs) for strength training, where training to volitional fatigue maximizes results but increases injury risk. This study proposes a volitional fatigue monitoring system to assist PTs in preventing fatigue-induced injuries. The system utilizes electromyography (EMG) with features derived from RMS and IEMG signals, with Random Forest classification method. Outputs are displayed on an OLED screen, LED lights, and a website via the WebSocket Protocol. EMG signal disturbances were mitigated with a filter, a battery, and a sport band. Testing involved five subjects aged 20-22 with various arm strength and no exercise background. The test results show that the EMG sensor acquires data within the appropriate range. The system achieved a 91.43% accuracy in muscle fatigue detection and a 1.0284 second average computation time, and produced the expected outputs with 100% accuracy. Therefore, the proposed monitoring system is feasible and reliable for volitional fatigue monitoring.
Co-Authors Edita Rosana Widasari, Edita Rosana