Applications and limitations of independent component analysis for facial and hand gesture surface electromyograms
Ganesh R. Naik, Dinesh Kumar · Journal and proceedings of the Royal Society of New South Wales · 2007
In the recent past, there has been an increasing trend to use bhnd source separation (BSS) or independent component analysis (ICA) algorithms for biomedical data.This paper reviews the concept of ICA and demonstrates its usefulness and limitations in the context of surface electromyograms (sEMG) related to hand movements and facial muscles.In the first experiment ICA has been used to separate the electrical activity from different hand gestures.The second part of the study considers separating electrical activity from facial muscles.In both instances the surface electromyogram has been used as an indicator of muscle activity.The theoretical analysis and experimental results demonstrate that ICA is suitable for identification of different hand gestures using sEMG signals.The results identify the unsuitabihty of ICA when a similar technique is used for facial muscles with respect to different vowel classifications.