Surface EMG based hand gesture identification using semi blind ICA: validation of ICA matrix analysis.

Abstract

Surface electromyogram (sEMG) has numerous applications. It has been widely used in various biosignal and neuro rehabilitation applications. There is an urgent need for establishing a simple yet robust system that can be used to identify subtle complex hand actions and gestures for control of prosthesis and other computer assisted devices. Earlier work to identify the hand actions and gestures based on sEMG suffers from limitation that these are suitable for gross actions where there is only one prime-mover muscle involved and not suitable for small subtle and complex muscle contraction. This paper presents the hand gesture identification using sEMG decomposed using semi-blind independent co..