Muscle Fatigue Assessment Using Multi-sensing Based on Electrical, Mechanical and Acoustic Properties

This paper shows that a multi-sensing technique using electromyogram (EMG), mechanomyogram (MMG), and acousticmyogram (AMG) used to monitor the status of rectus femoris muscle over three states; minimal stress, moderate fatigue, and severe muscle fatigue. Test subjects need to do the designed exercise protocol to simulate these state conditions. The sensors are located at the rectus femoris muscle, and signals were recorded simultaneously. Analysis of signals is based on root mean square (RMS), mean power frequency (MPF), and power spectral density (PSD) plot were compared between the muscle state conditions. Results show that the RMS values of the muscle are increased as the contraction occurs, and the MPF signal is decreased for all sensing properties. On the other hand, the frequency signal is shifted to the left in the PSD plot as the muscle undergoes fatigued for all sensors. In conclusion, multi-sensing using EMG, MMG, and AMG are useful for assessing muscle fatigue condition. It also provide advantages over the single-measurement muscle assessment method.