Subtle hand gesture identification for HCI using temporal Decorrelation source separation BSS of surface EMG

Abstract

Hand gesture identification has various human computer interaction (HCI) applications. This paper presents a method for subtle hand gesture identification from sEMG of the forearm by decomposing the signal into components originating from different muscles. The processing requires the decomposition of the surface EMG by temporal decorrelation source separation (TDSEP) based blind source separation technique. Pattern classification of the separated signal is performed in the second step with a back propagation neural network. The focus of this work is to establish a simple, yet robust system that can be used to identify subtle complex hand actions and gestures for control of prosthesis and ot..