[Research on the surface electromyography signal decomposition based on multi-channel signal fusion analysis]

The decomposition method of surface electromyography (sEMG) signals was explored by using the multi-channel information extraction and fusion analysis to acquire the motor unit action potential (MUAP) patterns. The action potential waveforms were detected with the combined method of continuous wavelet transform and hypothesis testing, and the effective detection analysis was judged with the multi-channel firing processes of motor units. The cluster number of MUAPs was confirmed by the hierarchical clustering technique, and then the decomposition was implemented by the fuzzy k-means clustering algorithms. The unclassified waveforms were processed by the template matching and peel-off methods. The experimental results showed that several kinds of MUAPs were precisely extracted from the multi-channel sEMG signals. The space potential distribution information of motor units could be satisfyingly represented by the proposed decomposition method.