Design And Implementation Of Decision Support System For Rehabilitation Training Program Of Upper Limb Rehabilitation Robot

Stroke has become the main cause of death and disability among adults in my country.With the development of medicine,the fatality rate of stroke has been suppressed to a certain extent,but the disability rate remains high,which brings great impact to the patients themselves,their families and society.With the rapid development of robotics and artificial intelligence technology,the application of rehabilitation robots and intelligent reasoning technology to clinical rehabilitation treatment has been widely recognized and has become one of the research hotspots,which is not only conducive to improving the rehabilitation effect of patients,but also saving family manpower,time,economic costs,and can reduce the labor intensity of rehabilitation physicians,alleviate the social problems of the shortage of rehabilitation physicians.In view of the fact that more than 85% of stroke patients are accompanied by upper extremity dysfunction,it is important to carry out research on upper extremity rehabilitation robots with important theoretical significance and demand background.This paper aims at the current status of upper extremity rehabilitation robots lacking rehabilitation quantitative evaluation and rehabilitation training program decision support system.Relying on the 6-DOF upper extremity rehabilitation robot independently developed by the team,a set of rehabilitation training program decision support system is developed to assist doctors Patients with upper limb motor dysfunction make decisions on rehabilitation training programs.The main research work of the thesis is as follows:1.Combining the theory of upper limb rehabilitation medicine,and fusing five evaluation indexes of joint range of motion,muscle tension,sensory function,Brunnstrom motor function and muscle strength,a five-dimensional upper limb motor function evaluation model was constructed.The model comprehensively reflects the patient’s upper limb motor function,and can comprehensively evaluate the upper limb motor function of different patients and patients in different rehabilitation periods.2.Combining the advantages of production rule notation and object-oriented knowledge notation,the knowledge base of upper limb rehabilitation medicine is constructed using compound knowledge notation.The knowledge base uses object-oriented knowledge as a carrier,strengthens knowledge connections through rules,and has the characteristics of clear structure,easy development and maintenance,and good scalability.3.Aiming at the uncertainty of the patient’s condition and the diversity and complexity of the rehabilitation training program formulation process,a fuzzy inference algorithm is proposed to realize the automatic interpretation of the rehabilitation training program.This method uses conflict resolution strategies to set thresholds to improve the efficiency of forward reasoning,and at the same time,uses the maximum membership method to defuzzify.The results show that the automatic interpretation of upper limb rehabilitation training programs can be realized based on fuzzy inference algorithm.4.With Intelli J IDEA as the system integrated development environment,Java as the system development language,and My SQL as the data management development tool,the development of the decision support system for the rehabilitation training program of the upper limb rehabilitation robot was completed.The test results of 30 clinical cases show that the upper limb rehabilitation training program automatically deduced by the system for the target patient is basically consistent with clinical diagnosis and treatment,and it can assist doctors in making decisions on rehabilitation training programs for patients with upper limb motor dysfunction.