The exaction of motor unit action potential from multi-channel SEMG signals

It has been demonstrated that the multi-channel SEMG allows assessment of anatomical and physiological individual motor unit characteristics. The motor unit action potential(MUAP) can be decomposed from SEMG to obtain these properties. This paper presented a method to exact MUAP from multi-channel SEMG. The firing instants of each motor unit(MU) were separated by K-means clustering Convolution Kernel Compensation(KmCKC) method, then the Spike Triggered Averaging(STA) technology was employed to reconstruct MUAP with firing instants as triggers. All of 10 MUAP templates have been successfully exacted with the proposed method. Simulation results demonstrate the efficiency and accuracy of the approach. This approach potentially offers a tool to sensitively obtain neuromuscle disorder and could more accurately guide advances in the evaluation of rehabilitation.