The Research On Simulation And Control System Of Brain Controlled Lower Extremity Rehabilitation Exoskeleton

Brain control technology is a human-computer fusion control system developed through the brain-computer interface(BCI).It uses the mind and thoughts of the brain as a control signal source.Lower extremity exoskeleton is a wearable intelligent electromechanical system that can enhance the body functions of the wearer and perform some special tasks.As one of them,lower extremity rehabilitation exoskeleton is mainly used to assist patients to walk and complete physical rehabilitation training.The cooperation of these two technologies can help patients who lose their ability to exercise due to the obstacle of brain motion control circuits to operate the exoskeleton through EEG signals,help them to rehabilitate training,so that they have a certain ability to exercise and take care of themselves.Bring new hope to them and reduce the burden on society and the family.This article first introduced the physiological structure of the human lower extremity and analyzed the gait.Based on this,the motion range and degree of freedom of the exoskeleton joints were determined,and the exoskeleton structure design and gait planning were completed.A kinematic and dynamic model of the lower extremities exoskeleton was established,and the motion trajectories and joint torque of each joint were obtained by solving the model.The simulation analysis of the lower extremity exoskeleton by Adams is carried out,which verifies the feasibility of exoskeleton structure design and the correctness of modeling.It provides a theoretical basis for the choice of driving mode,joint trajectory planning and control system.In order to achieve EEG control of external skeleton,the acquisition and processing methods of EEG signals were studied.The non invasive method of EEG acquisition is selected,and the Ear Reference is used to preprocess the pseudo trace.Then the optimal feature mode is obtained by the wavelet transform,which provides the distinct input data for the next BP neural network classification processing to realize the classification prediction of the exoskeleton movement in different directions.The sample training and experimental test are designed,and a high recognition rate is obtained in the classification and recognition of EEG signals.The control system of lower extremity rehabilitation exoskeleton system was constructed.The design of PC terminal control software is completed and the functions of communication,control and monitoring are realized.A special database is set up to save the related data in real time,which lays the foundation for the later realization of the viewand diagnosis function;the recognition of the EEG intention is completed;the exoskeleton control program of the AVR MCU is compiled.In addition,two sets of control methods have been developed,that is,a fixed training plan and active control by using brain control instruments to meet different rehabilitation training tasks.According to the above requirements,the appropriate hardware was selected to build a lower extremity exoskeleton experimental platform.The response speed and active control test of the whole system are tested.The experimental results are analyzed and the expected goal is reached.