基于运动想象脑电的上肢康复机器人

Upper-limb Rehabilitation Robot Based on Motor Imagery EEG

针对脑中风偏瘫患者的康复训练,设计了一种基于运动想象脑电的上肢康复机器人系统.首先,利用肢体运动3维动画刺激患者进行运动想象并通过USB脑电放大器采集运动想象脑电信号;然后,采用小波包算法进行特征向量的提取,并通过基于马氏距离的线性判别分类器分类:最后,PC利用虚拟现实技术进行视觉反馈,同时控制康复机器人.该系统使用患者上肢的运动想象脑电信号直接控制康复机器人进行训练,在很大程度上促进了运动神经功能的康复.6名受试者在该系统上进行了长时间的在线实验,初步证明了该系统的可行性.

For the rehabilitation training of hemiplegia patients caused by stroke,an upper-limb rehabilitation robot system based on motor imagery electroencephalography（EEG）is designed.Firstly,three-dimensional animation is used to stimulate the patient to imagine the upper-limb movement,and EEG signal is acquired by EEG amplifier via universal serial bus（USB）. Secondly,eigenvector is extracted by wavelet packet transform（WPT）,and linear discriminant analysis（LDA）classifier based on the Mahalanobis distance is utilized to classify the pattern.Finally,PC gives the visual feedback information based on virtual reality and controls the rehabilitation robot.The patient＇s upper-limb motor imagery EEG is used to control rehabilitation robot directly and it can accelerate the recovery of motor nerve function.Six subjects have been tested for a long time using this system.The results show the feasibility of the whole system.