Design And Analysis Of Auxiliary Weight Reduction Multi-Posture Lower Limb Rehabilitation Robot System

With the aging of society,the number of patients with lower limb dysfunction caused by stroke is increasing rapidly.In order to meet the rehabilitation needs and training objectives of different patients,this paper designed an auxiliary weight reduction multiposture lower limb rehabilitation robot,and its system was designed and analyzed.The main research contents of this paper are as follows:Firstly,according to the motion characteristics of each lower limb joint,the overall mechanism model of the assisted weight reduction multi-posture lower limb rehabilitation robot was established,and the structure of the lower limb training module and the auxiliary suspension module were designed.Meanwhile,the embedded distributed control system is constructed based on STM32 main control PCB hardware platform.Then the humancomputer interaction system is designed according to the principle of human-computer compatibility.And based on Choquet fuzzy integral embedded motor function rehabilitation assessment.Secondly,combined with the artificial rehabilitation mode,the combined motion trajectory of the robot under various posture is planned.Based on lower limb kinematics analysis,Monte Carlo method was used to determine the space boundary of patients with variable trajectory,and combined with the characteristics of Archimedean helix for safe expansion of trajectory radius,the trajectory planning of sitting position gradient circle was carried out.At the same time,the lower limb gait trajectory was collected based on the inertial motion trajectory capture instrument,and BP neural network was used to calibrate the reliability of the preprocessed multi-period trajectory,and the single period gait trajectory model was established.Then,in order to restrain the interference of external uncertain factors,the dynamics model of the lower limb rehabilitation robot was established.Based on the adaptive iterative learning control strategy,the trajectory tracking accuracy of the lower extremity auxiliary training module is improved step by step.At the same time,a hybrid force/position control strategy based on RBF fuzzy neural network was proposed for the unidirectional force of the rope.Torque synthesis method was used to compensate the centroid position before gait training,and the force closed loop was used to maintain the centroid balance of the patients.Finally,the prototype and hardware system of the lower limb rehabilitation robot are built.Experiments of straight pedaling trajectory in sitting position,gradual circle trajectory and gait trajectory in standing position were carried out,and the root mean square error of each joint was used to evaluate the trajectory tracking performance,and the rationality of the structural design and the feasibility of the control strategy of the rehabilitation robot were verified.