Estimation of single motor unit conduction velocity from surface electromyogram signals detected with linear electrode arrays

This work addresses the problem of estimating the conduction velocity (CV) of single motor unit (MU) action potentials from surface EMG signals detect ed with linear electrode arrays during voluntary muscle contractions, in id eal conditions, that is without shape or scale changes of the propagating s ignals and with additive white Gaussian noise, the maximum likelihood (ML) is the optimum estimator of delay. Nevertheless, other methods with computa tional advantages can be proposed; among them, a modified version of the be amforming algorithm is presented and compared with the ML estimator. In rea l cases, the resolution in delay estimation in the time domain is limited b ecause of the sampling process. Transformation to the frequency domain allo ws a continuous estimation. A fast, high-resolution implementation of the p resented multichannel techniques in the frequency domain is proposed. This approach is affected by a negligible decrease in performance with respect t o ideal interpolation. Application of the ML estimator, based on two-channe l information, to ten firings of each of three MUs provides a CV estimate a ffected by a standard deviation of 0.5 ms(-1); the modified beamforming and ML estimators based on five channels provide a CV standard deviation of le ss than 0.1 ms(-1) and allow the detection of statistically significant dif ferences between the CVs of the three MUs. CV can therefore be used for MU classification.