Adaptive spatio-temporal filtering of multichannel surface EMG signals
Determining the conduction velocity of motor unit action potentials is one of the most important problems in surface electromyography. The estimate of one average conduction velocity value depends on a variety of uncontrollable factors. More meaningful information is obtained from the estimation of the distribution of the different delays in the myoelectric signals. A solution to the problem is the separation and characterization of the individual components propagating at different velocities. A technique, based on surface electrode array recording, is proposed to estimate motor unit conduction velocity distribution. The method consists in the identification of the single action potentials in the time scale domain (with the continuous wavelet transform) and in the estimation of their conduction velocities based on the beamforming algorithm. The performances of the technique have been evaluated using simulated and real myoelectric signals. The results demonstrate that the technique is accurate and reliable. The method may be useful for the diagnosis of neuromuscular disorders, for the monitoring of muscle fatigue and for noninvasive investigation of individual motor units.