Adaptive trajectory planning of lower limb rehabilitation robot based on EMG and human-robot interaction

Abstract

Rehabilitation robots have been widely used in clinical rehabilitation in stroke subjects. The safety and comfort in rehabilitation training still are affected by many problems, however, such as the single rehabilitation training mode, the poor human-robot interaction and adaptability. In this paper, an adaptive trajectory planning method of lower limb rehabilitation robot based on surface Electromyography (sEMG) signal and interactive force (IF) is proposed to improve the human-robot interaction and adaptability. Firstly, the envelope difference method is used to identify flexion or extension of the lower limb based on the surface EMG signals from biceps femoris and vastus lateralis muscles; Secondly, the sEMG-IF fusion model is established on the plantar pressure and recognition result of flexion or extension with logical reasoning, and then the velocity trajectory of the robot can be planned with the model; Meanwhile, the evaluation of muscle activity level is introduced to adjust the robot's auxiliary coefficients and modify the velocity trajectory adaptively. In this paper, the corresponding three velocity trajectories of the robot were planned based on EMG signals during the three periodic movements. The result showed that the proposed method is feasibility and effectiveness.