Forehead sEMG signal based HMI for hands-free control

A hands-free method is proposed to control an electric powered wheelchair(EPW)based on surface electromyography(sEMG)signals.A CyberLink device is deployed to obtain and analyze forehead sEMG signals generated by the facial movements.The autoregressive(AR)model is used to extract sEMG features.Then,the back-propagation artificial neural network(BPANN)is proposed to recognize different facial movement patterns and improved by Bayesian regularization and Levenberg-Marquardt(LM)algorithm.A sEMG based human-machine interface(HMI)is designed to map facial movement patterns into corresponding control commands.The experimental results show that the method is simple,real-time and have a high recognition rate.