Analysis of surface EMG signals in biceps curls using maximum singular value estimation

In this work, an attempt has been made to analyze surface electromyography signals (sEMG) by estimating maximum singular value. sEMG signals are recorded from biceps brachii muscles of 50 healthy volunteers during repetitive elbow flexion and extension exercise. Maximum singular values are estimated from the signals. The results show a decrease in MSV at the point of first muscle discomfort experienced by subjects. For most of the subjects, the point of first discomfort occur in fourth and fifth regions of the time axis. It appears that this method can be used to analyze progress of muscle condition towards fatigue.