Abstract: To improve the training efficiency of Motor Imagery (MI) under visual guidance and the classification accuracy of Brain-Computer Interface (BCI), the influence of Virtual Reality (VR) environment on MI training and the differences of ElectroEncephaloGram (EEG) classification models under different visual guidance were studied. Firstly, three kinds of 3D hand interactive animation and EEG acquisition program were designed. Secondly, in the rendering environment of Helmet-Mounted Display (HMD) and planar Liquid Crystal Display (LCD), the left hand and right hand MI training was conducted on 5 healthy subjects, including standard experiment (the single experiment lasted for 5min) and long-time experiment (the single experiment lasted for 15min). Finally, through the pattern classification of EEG data, the influence of rendering environment and content form on classification accuracy was analyzed. The experimental results show that there is a significant difference in the presentation of HMD and LCD in visual guided MI training. The VR environment presented by HMD can improve the accuracy of MI classification and prolong the duration of single training. In addition, the classification model under different visual guidance content is also different. When the testing samples and training samples have the same visual guidance content, the average classification accuracy is 16.34% higher than that of different samples.

Key words: Brain-Computer Interface (BCI), Motor Imagery (MI), visual guidance, Virtual Reality (VR), ElectroEncephaloGram (EEG)

摘要： 为提高视觉指导下运动想象（MI）的训练效率和脑机接口（BCI）的分类准确率，研究了虚拟现实（VR）环境对MI训练的影响以及不同视觉指导下脑电（EEG）分类模型的差异。首先，设计了三种三维手部交互动画及其EEG采集程序；然后，分别在头戴式头盔（HMD）和平面液晶屏（LCD）的呈现环境下，对5名健康被试进行了标准（单次实验5min）和长测（单次实验15min）两种实验方案的左右手MI训练；最后，通过对EEG数据的模式分类，分析了呈现环境和内容形式对分类准确率的影响。实验结果表明，在视觉指导的MI训练中，HMD与LCD的呈现方式存在显著性差异。HMD所呈现的VR环境能够提高MI分类准确率，延长单次训练时长；此外，不同视觉指导内容下的分类模型存在较大差别，当测试样本与训练样本为同一视觉指导内容时，其平均分类准确率较之不同情况高出16.34%。

关键词: 脑机接口, 运动想象, 视觉指导, 虚拟现实, 脑电