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@article{204339,
        author = {Abhishek Jangid and Rahul Samre},
        title = {Operator Fatigue Measurement Using Electromyography},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {1583-1587},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=204339},
        abstract = {Muscle fatigue is a critical issue in industries and transportation systems where operators perform repetitive physical tasks for prolonged durations. Fatigue leads to reduced muscle strength, slower reaction time, decreased efficiency, and increased risk of accidents. This paper presents the development of a low-cost, real-time fatigue monitoring system using Electromyography (EMG). The system utilizes surface EMG sensors, Arduino Uno, and a computer interface to capture, process, and visualize muscle activity. EMG signals are filtered, rectified, and analysed using Root mean Square (RMS) techniques to evaluate muscle effort and fatigue levels. Experimental results demonstrate that increasing load and duration significantly increase muscle activation and fatigue. The developed system is simple, economical, and suitable for industrial, automotive, and healthcare applications.},
        keywords = {EMG, Muscle Fatigue, Arduino, Signal Processing, Real-Time Monitoring, Operator Safety.},
        month = {June},
        }