Analysis of surface EMG signals during dynamic contraction using Lempel-Ziv complexity

In this work, an attempt has been made to analyze progression of muscle fatigue in surface electromyography (sEMG) signals by estimating the complexity. The sEMG signals are acquired from biceps brachii of 50 healthy volunteers during dynamic contraction. The pre-processed signals are segmented into non-overlapping epochs of various sizes (500ms, 750ms and 1000ms) and Lempel-Ziv Complexity (LZC) is computed for each epoch. The linear regression technique is used to track the slope variations of LZC. The values of LZC show a decreasing trend during the progression of muscle fatigue. The magnitude of negative trend remained nearly constant irrespective of epoch size. Further, inter-subject variability of LZC measure is found to be minimum. The results shows that this method is useful in analyzing progression of muscle fatigue during dynamic contractions.