Extracting Motor Unit Firing Information by Independent Component Analysis of Surface Electromyogram: A Preliminary Study Using a Simulation Approach

Decomposition of electromyogram (EMG) provides a valuable means of obtaining motor unit recruitment and firing rate information. The feasibility of decomposing surface EMG signals into their constituent motor unit action potential (MUAP) trains using independent component analysis (ICA) was examined using simulated EMG data. Surface EMG signals detected with an array of nine electrodes were simulated when nine motor units were active. The electrodes were positioned in three different locations with respect to muscle fiber orientation. It was found that ICA based on an instantaneous mixing model was not able to separate all the MUAP trains due to shape variations and time delays between the surface action potentials detected at the different electrode locations. However, from certain independent components, the firing information of a very limited number of motor units could be obtained. This suggests that ICA based on an instantaneous mixing model may yield firing rate information of a small number of motor units from surface EMG signals recorded at relatively high force levels. However, to obtain more information, blind source separation techniques addressing a more complex convolutive mixing model are required. Similar results were obtained for each of three different electrode locations and orientations.