Surface Electromyography Signal Analysis for Detecting Muscle Fatigue During Grasping Exercises

This study aims to identify the onset and progression of muscle fatigue during gripping exercises using surface electromyography (sEMG) signals. This research differs from previous studies in that it considers static and dynamic conditions, analyzing signals from three forearm muscles across a range of force levels. A novel approach combines dynamic and static data to comprehensively view muscle behavior. Muscle fatigue was assessed through feature extraction, including zero crossings (ZC), mean frequency (MNF), root mean square (RMS), and median frequency (MDF), with the MDF/RMS ratio introduced as a sensitive indicator of fatigue, especially at higher loads. These findings demonstrate the effectiveness of sEMG in monitoring fatigue and optimizing muscle performance, providing insights that inform the development of more effective training and rehabilitation strategies.