Trajectory generation for myoelectrically controlled lower limb active knee exoskeleton

Abstract

Aim of this paper is to generate joint angle trajectory of knee joint and fed it to a myoelectric controlled lower body exoskeleton to regenerate lost gait pattern. EMG signal of six different lower limb muscles has been acquired and fused using standard fusion technique discarding spurious data. From the fused EMG data, different gait parameters like stride time, gait phase etc has been calculated. Joint trajectory during a gait cycle is obtained from Kinect sensor that can extract comprehensive gait information from all parts of the body. Joint angle obtained from kinect is combined with the gait parameters acquired from EMG and together they will be fed to a robotic lower limb exoskeleton. As the exoskeleton joints are fed with true joint angle data of the user and the joints are driven by users own intention signal, functioning, control and acceptability of the exoskeleton device is much more to a 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.