Research on Interactive Control Algorithms for Lower Limb Exoskeleton Rehabilitation Robots

Lower limb exoskeleton rehabilitation robots represent an important development direction in modern rehabilitation technology. By integrating various sensors and control algorithms, these robots effectively enhance the specificity and efficiency of rehabilitation training. This paper systematically analyzes several widely used control methods, including position-based, force feedback, bioelectrical signal, and intelligent control strategies. Each strategy has its unique features and addresses different issues in the interaction between the robot and the patient, thereby improving the effectiveness and efficiency of rehabilitation training. For instance, position control provides stability and repeatability, force control ensures compliance, bioelectrical signal control offers rapid responsiveness, and intelligent control exhibits adaptability. Future research will focus on combining the advantages of different strategies to develop composite control methods that enable more efficient and personalized rehabilitation training, enhancing patient recovery outcomes and experiences