Research of hand gesture identification of sEMG based on SCICA

Traditional hand gesture identification systems require designers to use multiple serial interfaces or multiplexer as tools to record surface Electromyography (sEMG). These ways lead to complicated circuit connection and unreliability of hardware. It is therefore imperative to have good methods to explore a more suitable design choice, which can avoid the problems mentioned above as more as possible. This paper presents a hand gesture identification system of sEMG based on Single Channel Independent Component Analysis (SCICA) which can avoid the problems mentioned above and reduce the noise which accompanied with sEMG signal. It also provides high-level modeling, programming methods and running results for this system in terms of software and hardware. More specifically, real time communication and identification are accomplished accurately between the hand and identification system by taking advantage of USB interface and VC++ s2008. This system also can manage the historical sEMG signals by using database. Furthermore, it has such advantages as low cost and easy to maintain and promote.