Muscle fatigue monitoring and analysis system: Myosense

This study presents a software tool for analyzing forearm muscle fatigue in high-performance tennis players using electromyographic (EMG) signals. The system integrates a Myo armband for data acquisition, entropy-based feature extraction, and a Support Vector Machine (SVM) classifier to distinguish between fatigue and non-fatigue states. Experimental validation achieved up to 80.02% Average accuracy. The software automates signal processing, enhances reproducibility, and enables real-time monitoring. Its applications extend to wearable sports technology, training optimization, and rehabilitation. Future work includes integration with embedded systems and expanding its use in other biomechanical and medical research areas.