Limitations and applications of ICA in facial sEMG and hand gesture sEMG for human computer interaction

Abstract

In the recent past, there has been an increasing trend of using Blind Signal Separation (BSS) or Independent Component Analysis (ICA) algorithm for bio medical data, especially in prosthesis and Human Computer Interaction (HCI) applications. This paper reviews the concept of BSS and demonstrates its usefulness and limitations in the context of surface electromyogram related to hand movements and vowel classification. In the first experiment ICA has been used to separate the electrical activity from different hand gestures. The second part of our study considers separating electrical activity from facial muscles during vowel utterance. In both instances surface electromyogram has been used as..