Multi-step Independent Component Analysis for Removing Cardiac Artefacts from Back SEMG Signals

The Electromyogram (EMG) signals recorded from the back muscles often contain large electrocardiogram (ECG) artefacts. For better interpretation of these SEMG signals, it is essential to remove ECG artefacts. This paper reports research conducted to address the problem of removing ECG artefacts from SEMG recordings using new approach of Independent Component Analysis (ICA) called Multi-step ICA. The technique isolates the ECG artefact first and then removes the ECG artefact from each channel and solves permutation problem simultaneously. The results have been validated using standard deviation reduction of the normalised RMS amplitude of the data after separation process. The results demonstrate that this new proposed technique is successful in removing ECG artefacts from SEMG signals.