Multichannel fused EMG based biofeedback system with virtual reality for gait rehabilitation

Aim of this paper is to develop an EMG based biofeedback system using a virtual reality platform which will help in gait rehabilitation. A low power multichannel EMG acquisition unit has been developed to acquire EMG of six different muscles of the lower limb. EMG from different channels are fused using Bayesian fusion technique and spurious data has been discarded. From the fused EMG data, we calculate different gait parameters like stride time, gait phase etc. Joint trajectory during a gait cycle is obtained, digitized and combined with the gait parameters acquired from EMG. Together they are fed to a VR human model. Just like a person walks, the same EMG and trajectory data being fed to the model, it walks too mimicking the gait of the user, with the same speed, thus providing biofeedback to the user. The system has massive application in gait rehabilitation for post-stroke patients, people suffering from cerebral palsy and other neuro muscular gait defects, amputees etc.