Rigid-flexible Coupling Design And Force/position Control Of Pneumatic Waist Rehabilitation Robot

Low back pain patients are growing more common as the population structure and lifestyle change,and the tendency of younger patient groups is becoming more apparent.Low back rehabilitation exercises that are scientifically validated and standardized play an important role in the prevention and treatment of non-specific low back pain.This paper starts with the theory of motor rehabilitation,then conducts specific research on three parts of the lumbar rehabilitation robot: configuration design,lumbar curve fitting,and force-position control,to address the problems of insufficient adaptability and poor rehabilitation effect of the existing lumbar rehabilitation robot.To begin,this paper analyzed the characteristics of lumbar motion and rehabilitation training activities,and integrated the theory of sports rehabilitation to propose a lumbar rehabilitation robot configuration that conforms to the laws of human lumbar motion,adapts to the lumbar curvature of different patients,and has certain flexibility.Secondly,approaches for lumbar spine curve fitting reconstruction and morphological optimization were proposed.Polynomial interpolation is utilized to determine the goal lumbar curve,and the B spline curve is used to reconstruct the target lumbar curve.Smooth curve optimization is achieved by optimizing the selection of curve control points,which takes use of the local controllability of the B spline curve.Thirdly,gray correlation and multivariate correlation analysis are used to realize the human-machine interaction force-position perception based on the flexible sensor of robot.A fuzzy PID-based hybrid control approach for the rehabilitation robot force level is presented based on the motion and control needs of the lumbar rehabilitation robot,and simulation tests are undertaken to evaluate the control plan’s effectiveness.Finally,the proposed lumbar rehabilitation robot’s principal prototype was experimentally verified for each performance.The testing findings were assessed to confirm the robot’s motion performance and the control strategy’s effectiveness.