Development of a sEMG-based torque estimation control strategy for a soft elbow exoskeleton

Abstract

Motor dysfunction has become a serious threat to the health of older people and the patients with neuromuscular impairment. The application of exoskeleton to motion assistance has received increasing attention due to its promising prospects. The major contribution of this paper is to develop a joint torque estimation control strategy for a soft elbow exoskeleton to provide effective power assistance. The surface electromyography signal (sEMG) from biceps is utilized to estimate the motion intension of wearer and map into the real-time elbow joint torque. Moreover, the control strategy fusing the estimated joint torque, estimated joint angle from inertial measurement unit and encoder feedback signal is proposed to improve motion assistance performance. Finally, further experimental investigations are carried out to compare the control effectiveness of the proposed intention-based control strategy to that of the proportional control strategy. The experimental results indicate that the proposed control strategy provides better performance in elbow assistance with different loads, and the average efficiency of assistance with heavy load is about 42.66%.