Assist-as-needed And Active Rehabilitation Control Technology Of Bilateral Mirror Upper Limb Rehabilitation Robot

Cerebral apoplexy,also known as "stroke" or "cerebrovascular accident",is caused by sudden cerebrovascular rupture or blocked blood vessels can not normally flow into the brain and cause brain tissue damage,the high incidence of stroke,high mortality and high morbidity,serious damage to the patient’s health and threaten their life,giving patients,family,society and country to bring heavy burden,stroke has become the leading cause of death in China,and there is a serious shortage of rehabilitation therapists in China at the present stage.Facing the growing demand for rehabilitation,rehabilitation assisted robot has emerged as a new type of rehabilitation assisted medical equipment.However,for physical therapy,whether assisted by a therapist or a robot,because the movement instruction to the patient is entirely provided externally,so patients have little involvement throughout treatment,and this involuntary rehabilitation task has been pointed out as losing value.This paper takes the bilateral upper limb mirror rehabilitation robot independently designed by the research group as the research platform.In order to assist patients in completing rehabilitation training tasks and improve the degree of patients’ participation in the rehabilitation training process,the control strategy of the upper limb rehabilitation robot is studied and proposed.The main work contents are as follows:1.By using D-H parameter method and Lagrange method,the kinematics and dynamics modeling of the bilateral upper limb mirror rehabilitation robot is carried out.In order to improve the precision of system control,by means of rehabilitation robots each joint friction experiment,using the friction model,identify the coefficient and friction compensation in the control program,which laid a foundation for the design of the rehabilitation robot control strategy.2.This paper proposes an assist-as-needed control strategy based on human upper limb model,which can provide appropriate assist force in different positions of the patient’s upper limb through the movement information of the patient’s upper limb.Compared with the traditional controller,it has a larger controllable range and can assist the patient more accurately.3.In the process of rehabilitation training,in order to solve the patients because of the existence of assist force to produce slack problem,put forward a kind of active rehabilitation based on Gaussian Mixture Model(GMM)control strategy,using GMM algorithm to identify the patient current position of the rehabilitation task stage,so as to provide appropriate auxiliary force according to the control strategy.