Design And Implementation Of Hardware System For Hand Function Rehabilitation Training Robot

With the increasing of degree of aging in China,stroke has been one of the major diseases which endanger the life security and quality of life seriously.Stroke patients often suffer from the movement disability of upper and lower extremity due to the damage of central nervous system and need rehab through rehabilitation training.Owing to the late start of rehabilitation medical treatment in China,professional rehabilitation therapists and rehabilitation institutions are seriously inadequate.At the same time,since the lack of modern rehabilitation medical equipment,the rehabilitation needs of patients cannot be met through traditional manual or simple medical equipment.Rehabilitation robots,which is a subject of multidisciplines such as rehabilitation medicine,computers,and robotics,provide a new approach for the development of China's rehabilitation medical industry.This thesis aims at the current problems in the research of hand-functioning rehabilitation robots at native and abroad,such as over simple training model and unreasonable functional structure,proposes a multi-training mode hand-function rehabilitation training robot with highly flexible and refined training structure.The main studies include:According to the basic theory of stroke and the causes of hemiplegia,and human brain plasticity theory,this thesis gives the mechanical design scheme for machine hand and controller in the robot.In the design of the electrical system of the robot,this thesis takes the STM32 micro-control as the core.It gives the circuit design of the motor control circuit board,the pressure acquisition circuit board and the main control circuit board respectively,and explains the selection basis of some components and core circuit design principles.In order to enhance the stability of the robot,the Savitzky-Golay smoothing filter is used to smooth the motor position data and pressure data of each motor,and the filtering effect is verified by MATLAB.Based on the Brunnstrom evaluation method of hemiplegia,this thesis proposes three kinds of rehabilitation training modes: passive training mode,assistant training mode and active training mode.It also designs and implements the core algorithms of each training mode.Among the three training mode,The motor motion adjustment algorithm based on human biological characteristics can regularize the motion process of the motor in the passive training mode so as to achieve the intended rehabilitation purpose;In assistant training and active training mode,because the patient's finger pressure collection environment is different,in order to detect the patient's movement intention accurately,the exercise intention detection algorithm based on pressure threshold and pressure change rate are proposed in this thesis.The preliminary experiments prove that the robot proposed in this thesis can effectively help stroke patients to undergo rehabilitation training,which greatly enhances the willingness and subjective initiative of stroke patients for rehabilitation training,and also minimizes the work intensity of rehabilitation therapists.