Lower limb intelligent rehabilitation robot based on human-gait coupling, spatiotemporal gait sensing, and fuzzy PID control

For individuals with dyskinesia, postoperative walking rehabilitation is crucial, and lower limb exoskeletons provide effective training assistance. This paper proposes a method for designing a lower limb exoskeleton based on sensor feedback and human-robot gait simulation. Firstly, a mathematical model of lower limb motion and an exoskeleton robot model are designed based on hip/knee joint motion and gait mechanisms. Secondly, gait simulation is performed via human-robot coupling, with a comparative analysis of lower limb muscle dynamics during walking. Hip/knee motion data is converted into motion function curves for dynamic simulation verification. Subsequently, a brushless motor drive control system for the lower limb exoskeleton is developed using Simulink, and simulation experiments are conducted for position, speed, and torque control. Finally, patient walking experiments using membrane pressure and pose sensors analyze hip/knee and plantar pressure data, enabling output adjustment feedback and closed-loop torque control of the exoskeleton.