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Research On Human-computer Interaction Of Upper Limb Rehabilitation Based On EMG Signal And Posture Capture

Posted on:2021-04-20Degree:MasterType:Thesis
Country:ChinaCandidate:L ChenFull Text:PDF
GTID:2428330602481522Subject:Mechanical engineering
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The aging of population and the shortage of professional medical rehabilitation personnel make the limited medical resources difficult to meet the huge demand of medical and health services.The upper limb exoskeleton rehabilitation robot is the product of the fusion of robotics and rehabilitation medicine.The upper limb rehabilitation robot can provide accurate and repeated upper limb training actions for stroke patients,reduce the heavy physical labor of medical staff,and assist patients to recover the upper limb movement function and normal life.The rehabilitation training of the upper limbs of stroke patients after operation is complex,and there are many deficiencies in the existing rehabilitation equipment.In this paper,a new six degree of freedom exoskeleton rehabilitation robot and human-computer interaction mode are designed for the rehabilitation training of upper limbs of stroke patients.In this paper,the development of upper limb rehabilitation robot technology at home and abroad and the rehabilitation technology of stroke patients are analyzed.According to the anatomical characteristics of the human upper limb and the proprioceptive neuromuscular facilitation(PNF),the rehabilitation needs of the upper limb of stroke patients are summarized.According to the needs,a new six degree of freedom rehabilitation robot for the upper limb exoskeleton is designed.The six degrees of freedom are respectively three degrees of freedom at the shoulder joint,one degree of freedom at the elbow joint and two degrees of freedom at the wrist joint.In addition,the electrical circuit and upper computer software of the system are designed.Innovative use of the support rotary bearing,so that patients can switch between the left and right upper limbs,to achieve a dual-purpose purpose.D-H parameter method was used to analyze the kinematics of the six degree of freedom upper limb rehabilitation exoskeleton robot.According to the particularity of medical devices,multiple safety mechanisms such as physical limit,electrical limit and software limit are designed.In order to ensure the safety of the upper limb rehabilitation training process,the upper limb posture capture technology based on inertial sensor is studied.Firstly,the method of using inertial sensor to calculate the upper limb attitude is studied.Then the hardware and software of mpu9250 motion sensor are designed.The Mahony filtering fusion algorithm is analyzed and studied.The three-axis accelerometer value,the three-axis angular velocity value and the three-axis magnetic field angle value are fused into a quaternion or a group of Euler angles.Two sensor nodes are installed on the arm to monitor the arm posture experiment,which verifies that the inertial sensor can monitor the arm posture of patients to improve the safety of rehabilitation training.In order to quantify the effect of upper limb rehabilitation training,rehabilitation doctors were assisted to develop rehabilitation training programs.The recovery of patients in rehabilitation training was evaluated by the intensity of sEMG signal.A multi-channel surface EMG synchronous acquisition system is designed and built.According to the characteristics of biological weak signal,the acquisition system mainly adopts two-stage amplification and two-stage filtering,multi-channel parallel,synchronous acquisition scheme.The intensity of signal was analyzed to evaluate the recovery of upper limb motor function.Sports function evaluation is an important part of rehabilitation,to ensure the safety of the treatment and training process,and to summarize the previous treatment results in stages,can better assist doctors to formulate the next stage of rehabilitation treatment plan.
Keywords/Search Tags:Upper limb exoskeleton rehabilitation robot, Kinematics, Motion capture, Surface electromyography signal, Motor function evaluation
PDF Full Text Request
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