An exploration of eliminating cross-talk in surface electromyography using independent component analysis

The purpose of this study was to explore the use of Independent Component Analysis (ICA) on surface Electromyography (EMG) data to distinguish between individual muscle activations due to its capabilities for signal separation. EMG data was gathered on seven participants using the Delsys Trigno Wireless EMG system. Participants performed specific movements which targeted the calves muscle group of the lower leg. EMG sensors were attached according to SENIAM recommendations and extra sensors were attached in non-recommended locations to achieve crosstalk. Signals were acquired using proprietary Delsys software and processed using the ICA algorithm in Matlab to explore crosstalk. Integrated EMG was calculated for all results using custom Matlab code. The results showed moderate levels of agreement between the mixed signals and the original signals (p < 0.01). However, further work is needed to determine the usefulness of the independent components.