Control Method for Lower Limb Exoskeleton Robot Based on Surface Electromyography Signals

Abstract

Against the backdrop of the continuous growth in global demand for medical rehabilitation, the research on control methods for lower limb exoskeleton robots is particularly important as key equipment to improve the quality of life of individuals with lower limb dysfunction. This article systematically reviews the research progress of control methods for lower limb exoskeleton robots based on surface electromyography (sEMG) signals. Firstly, the bioelectric properties of sEMG signals and their core advantage in motion intention recognition - the ability to capture muscle activation status 100-200ms in advance - were discussed. Subsequently, the key steps of sEMG signal processing and intent recognition algorithm were elaborated. This article focuses on control methods and provides a detailed review of traditional PID control, adaptive sliding mode control for high-precision trajectory tracking, variable impedance control for dynamically adjusting joint impedance based on the Hill muscle three-element model, multimodal fusion control combined with multi-source information such as sEMG and Inertial measurement unit (IMU) to enhance environmental adaptability, and Non-Convex Function Activated Anti-Disturbance Zeroing Neurodynamic(NC-ADZND) human-machine interaction control. By comparing experimental data and analyzing the advantages and limitations of various methods, the development direction of this field was finally discussed.