Design Of Hand Rehabilitation Robot Control System Based On Semg Feedback

With the advent of an aging population,the incidence of cerebrovascular diseases represented by stroke has increased sharply,and the number of elderly patients has increased significantly,causing a great burden on society and families.Stroke can cause patients with certain motor dysfunction,of which the hand is the most likely to cause damage.The hand rehabilitation robot can overcome the current shortage of medical resources and provide a new method for the hand rehabilitation treatment of stroke patients.The hand needs to complete very complex movements in daily life.In the rehabilitation training process,it is very important to train the grip strength of the fingers.The problem that needs to be solved is how to predict the main driving force of the patient and the rehabilitation robot.Control of human-machine contact force.This article conducts research on the above problems,and the specific work content is as follows:First,based on the human hand joint motion model,the mechanical structure and movement mode of the hand exoskeleton used in this paper are analyzed.Simplify the structure to get its geometric model,and use the geometric analysis method to establish the forward and inverse kinematics model of the hand exoskeleton structure;on this basis,the Lagrange equation is used to analyze the dynamics of the hand exoskeleton to obtain the motor drive The relationship between space,finger joint space and fingertip Cartesian space.Secondly,for the prediction of the patient's driving force,based on the correlation between surface electromyography(sEMG)and muscle contraction force,a regression relationship between multi-channel surface EMG characteristics and hand grip strength is established.Realize the decoding of the patient's active grip strength;optimize the selection of EMG features by analyzing the correlation between sEMG features and grip strength;use particle swarm optimization(Particle Swarm Optimization,PSO)to optimize the model parameters and improve the accuracy of the model;Finally,the effectiveness of the method is verified through experiments.Thirdly,in order to improve the accuracy of the control of the human-machine contact force of the rehabilitation robot and ensure the flexibility of the human-machine contact,the control outer loop realizes the tracking of the expected auxiliary force through the position-based impedance controller.Aiming at the problem of continuous change of human-machine contact impedance during rehabilitation training,a fuzzy impedance controller based on sEMG is proposed to achieve the adjustment of target impedance and reduce the steadystate error of the force;It adapts to the uncertain items of the compensation system modeling,and realizes the stable tracking of the trajectory based on the calculated moment method.A control simulation model is established based on Sumulink,and the effectiveness of the method is verified through simulation.Finally,build a hand rehabilitation robot control experiment system,including signal acquisition system,data processing system,rehabilitation robot control system.Collect the surface myoelectric signal of the subject,and use the method in this paper to carry out active grip strength estimation and human-machine contact force control to verify the effectiveness of the method.