EMG-based signal processing system for intepreting arm gestures

This paper presents an electromyographic-based (EMG-based) signal processing system for interpreting human arm gestures. To retain a constraint-free user's environment, EMG sensing is limited to three arm muscles. EMG signals are processed to attain parameters that are related to the muscles temporal activities. The attainment of these parameters through time constructs a unique signature for each particular gesture. Experimental investigation was carried out to examine the system's reliability in recognizing 12 arm gestures. The results show that the system can recognize the 12 gestures with a success rate of 96%.