Research On Motion Planning And Control Strategy Of Exoskeleton In Upper Limb Rehabilitation

Currently,rehabilitation training is the major treatment method for upper extremity motor dysfunction induced by nerve damage.As the number of stroke patients rises,so does the number of patients suffering from motor dysfunction caused by sequelae.Traditional rehabilitation therapy approaches based on rehabilitation physicians are increasingly challenging to meet actual demands due to a limited number of rehabilitation physicians.The advent of the upper limb rehabilitation robot introduces a novel approach to resolving the nerve difficulty that rehabilitation specialists face.Simultaneously,the development of the upper limb rehabilitation robot can significantly reduce the physical labor of rehabilitation specialists and improve the efficiency of rehabilitation therapy.The trajectory and control strategy have a substantial impact on the efficiency of exoskeleton-assisted rehabilitation training.An appropriate motion trajectory can increase not only treatment efficiency but also patient comfort.The function realization of the exoskeleton is directly determined by the control approach.The movement characteristics of the exoskeleton can be altered by modifying the exoskeleton’s control strategy,which impacts the implementation of the exoskeleton function and the results of the human-computer interface.As a result,the primary purpose of this study is to increase patient comfort while using an upper limb rehabilitation exoskeleton and to meet various exoskeleton control demands.This paper focuses on two aspects: exoskeleton motion planning and control strategies.It is proposed to develop a motion acquisition scheme based on visual recognition.The upper limb exoskeleton trajectory planning model is finished by BP neural network and the upper limb exoskeleton kinematic model.The model of the human motion decision-making process is realized with the BP neural network.The trained motion models of the wrist and elbow joints,respectively,implement the planning of the end trajectory and the constraints of the kinematic inverse solution.Simultaneously,the model outputs were optimized by boundary condition constraints and geometric constraints to adhere to upper limb kinematics rules.The exoskeleton’s control strategy is explored and constructed with the principles of impedance control and PID control,and the exoskeleton’s contact force feedback and position feedback are carried out by impedance control and PID control,respectively.To simulate the effect of ambient elements in the movement of the exoskeleton,the friction force and human impedance model are used to simulate and verify the different movement modes of the exoskeleton.The trajectory planning model of the upper limb exoskeleton is established by Matlab,and the performance of the planning results is demonstrated through measures such as error,correlation coefficient,and one way distance.By comparing the results to the human trajectory,the advantage of the similarity between the results and the human trajectory is confirmed.Matlab is used to create the upper limb exoskeleton control model,and the efficiency and applicability of the control strategy are demonstrated by the implementation of passive training,follow-up,and coordinated movement.