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

Abstract

This work addresses the problem of estimating the conduction velocity (CV) of single motor unit (MU) action potentials from surface EMG signals detected with linear electrode arrays during voluntary muscle contractions. In ideal conditions, that is without shape or scale changes of the propagating signals and with additive white Gaussian noise, the maximum likelihood (ML) is the optimum estimator of delay. Nevertheless, other methods with computational advantages can be proposed; among them, a modified version of the beamforming algorithm is presented and compared with the ML estimator. In real cases, the resolution in delay estimation in the time domain is limited because of the sampling process. Transformation to the frequency domain allows a continuous estimation. A fast, high-resolution implementation of the presented multichannel techniques in the frequency domain is proposed. This approach is affected by a negligible decrease in performance with respect to ideal interpolation. Application of the ML estimator, based on two-channel information, to ten firings of each of three MUs provides a CV estimate affected by a standard deviation of 0.5 m s(-1); the modified beamforming and ML estimators based on five channels provide a CV standard deviation of less than 0.1 m s(-1) and allow the detection of statistically significant differences between the CVs of the three MUs. CV can therefore be used for MU classification.

On the behavior of surface electromyographic variables during the menstrual cycle

“…These estimators were calculated for the channel with the highest signal amplitude (peak value) as follows: Conduction Velocity. We used the algorithm proposed by Farina et al (2001) for calculating CV from S-EMG signals acquired with an array of electrodes, with adaptations. This algorithm uses maximum likelihood estimation (MLE) and a generalization of the classical spectral waveform alignment algorithm (McGill and Dorfman 1984).…”

“…, K is the channel number, θ is associated with the temporal delay between adjacent channels-the actual inter-electrode temporal delay is given by (θ × f s ) −1 -and w[n] is white Gaussian noise. The basic waveform was estimated by aligning and averaging the signals that were measured in each of the K channels (Farina et al 2001) as follows:…”

Modeling and Identification of the Electrohysterographic Volume Conductor by High-Density Electrodes

“…In fact, no spatial information could be derived from the electrodes that are aligned orthogonally to the AP propagation direction. Note that, due to the preliminary line selection based on the interchannel signal similarity, the conduction velocity estimates in the selected line are more reliable [33].…”

Adjustments Differ Among Low-Threshold Motor Units During Intermittent, Isometric Contractions

“…3). Muscle fiber conduction velocity was estimated for each motor unit from the average action potentials with a multichannel method (Farina et al 2001(Farina et al , 2002. Three to six channels were used to estimate conduction velocity based on the criterion of a minimal change in shape of the action potential as determined by visual selection (Farina et al 2002).…”