The use of Independent component analysis on EMG data to explore cross-talk

The purpose of this study was to explore the use of Independent Component Analysis (ICA) on Electromyography (EMG) data to distinguish between individual muscle activations due to its capabilities of signal separation. EMG data was gathered on seven participants using the Delsys Trigno Wireless EMG system. Participants performed movements which targeted the quadriceps muscle group. EMG sensors were attached according to SENIAM recommendations and extra sensors were attached in non-recommended locations. Signals were gathered and passed through an ICA algorithm to explore crosstalk. The results showed moderate levels of agreement in mixed signals and original signals.