Estimation of average muscle fiber conduction velocity from two-dimensional surface EMG recordings

We propose a novel method for the estimation of muscle fiber conduction velocity (CV) from surface EMG recordings. The approach is based on the analysis of signals detected along a number of linear electrode arrays parallel to the fiber direction, thus collected by a bi-dimensional (2-D) array (matrix) of electrodes. The information provided by the 2-D array is used to derive a maximum likelihood estimator which can be applied to any number of signals and which may account for missing channels in the matrix. An iterative technique in the frequency domain for the estimation of the propagation delay is proposed to reduce the computational time and avoid the limit of resolution due to signal sampling. The method proposed is applied to signals collected from the biceps brachii muscle of eight healthy subjects during isometric, constant force contractions at 50% of the maximal voluntary contraction torque. It is shown that CV estimation standard deviation and sensitivity to electrode displacements significantly decrease by the application of the method proposed with respect to classic CV estimation techniques. The method promises to be a useful tool when average CV is estimated for muscle assessment and diagnostic purposes.