Hand mode online recognition system of electromyography prosthetic hand based on MYO

Surface electromyography (sEMG) is widely used in clinical diagnosis,rehabilitation engineering and human-computer interaction,etc.Aming at the problems of high cost of electrodes to control electromyography prosthetic hands,the difficulty in electrodes wear and poor operation flexibility,a MYO-based hand mode online identification system of electromyography prosthetic hands is designed.By collecting the sEMG of the human upper-limb-forearm and extracting 5 characteristic values in the time domain,8 real-time gesture recognition strategies are realized through the back propagation neural network.Experimental results show that the MYO-based gesture recognition canproduce bettergesture recognition results.The system can accurately identify the eight kinds of hand movements,and the average online recognition rate reaches 92%