A decomposition algorithm for surface electrode-array electromyogram

The purpose of the present study was to fully and reliably decompose surface electromyograms (s-EMGs) into their constitutive motor action unit potential trains (MUAPTs) at higher levels of contraction than that possible by using established methods. An algorithm for s-EMG signals decomposition based on preprocessing filters, independent component analysis (ICA), and on a template-matching technique was developed. In this study, it was demonstrated how ICA can be used successfully for solving overlaps of MUAPs. In each iteration of the algorithm, the action potentials of one motor unit (MU) could generally be separated from the others. Subsequently, using a template-matching technique, we were able to identify the action potential train of the selected MU. Results show that the algorithm satisfactorily decomposed the s-EMGs into their constitutive MUAPTs up to 30, 50, and even 60% maximum voluntary contraction (MVC). The results are in agreement with the generally accepted behavior of MUs firing rates.