Motor unit action potential number estimation in the surface electromyogram: wavelet matching method and its performance boundary

Given that the motor unit action potential (MUAP) originates at some distance below a standard surface electromyography (EMG) electrode, the basic shapes of surface MUAPs can ideally be represented by only a very small number of waveforms or wavelet functions. Based on this determination, we evaluate ways to estimate the number of MUAPs present in standard surface EMG records, using wavelet based matching techniques to identify MUAP occurrences. The reason for this approach is that estimates of the numbers of MUAPs are likely to be a more accurate reflection of the neural command to muscle than are current EMG quantification methods, which treat the EMG as a continuous signal. We further attempt to assess the accuracy and general applicability of wavelet based methods used for this purpose, and the performance boundaries of the counting methods are also explored. We show that the performance of wavelet matching methods is mainly determined by the MUAP superposition rate in the signal. To explore this prediction more directly, we compared the MUAP number estimation results by wavelet matching methods using a highly selective multiple concentric ring surface electrode and a standard single differential surface EMG electrode.