Human-computer interaction system design based on surface EMG signals

Abstract

Surface electromyography signals (SEMG) aquisition is a kind of multi-channel non-invasive detection method. In this paper, we designed a human-computer interaction system based on the multi-channel SEMG of hand motions. The system detects the forearm muscle multi-channel SEMG, the AR model is established to extract the signal eigenvalue and the artificial neural network classifier (BP) is utilized to distinguish the four different gestures that the results of pattern recognition are applied as the quad copter control signals. At last, the results of pattern recognition are used as control signal of aircraft to complete real-time interactive process.