Computer-assisted decomposition of the electromyograms

Analyses the scope of multimodal parametric searching (MPS) as a means for the decomposition of electromyograms (EMGs). The approach is based on a predefined set of signal sources that are described by some parameters. These signal sources are searched for in a superimposed signal by calculation of the Euclidian distance and by looking for its minimum. The signal sources are applied successively, according to the changes in their parameters, and peeled off at the minimum Euclidian distance found. The minima detected are then displayed in parametric space as a parametric representation. We show that such a technique is reliable enough for the decomposition of needle EMGs at low contraction forces. Applied to surface EMGs, it still discerns different phenomena, although not always with a direct relationship to reality. This is because of the method´s ambiguity, amplitude ratio dependency and a bias in the distribution of the detected signal components. Finally, we introduce a novel approach based on the wavelet transform and using the elements of the parametric search. Both approaches give comparable decomposition results when applied to the EMGs.