Extraction of EI and EDM muscle sources from surface electromyographic signals using delay estimation

Interference or a crosstalk from nearby muscles is a classic problem in surface electromyographic recordings. Most studies of crosstalk diminution have only focused on blind source separation techniques and spatial filtering of simulated signals. The aim of this study was to perform an extraction of the activity of index and little finger extensor muscles from the electromyographic mixtures recorded with a surface electrode array. The motor unit action potential were detected in the mixtures and classified according to an inter-electrode delay. The signal-to-interference ratio performance of the proposed method was higher than performance of the beamformer and the frequency JADE algorithms. The findings show that creation of a muscle action potential propagation model, required by beamformer, could be problematic. The proposed algorithm uses a generalized model and shows higher performance.