基于LabVIEW运动想象的脑机接口系统***◆

背景：基于事件相关电位的脑-机接口，可广泛应用于残障患者的康复，显示出其重要性和未来实现的可行性。 目的：提出基于LabVIEW环境下的运动想象脑-机接口系统的实现方案。 方法：研究的关键部分是视觉刺激器的设计和脑电特征信号的特征提取两部分。测试者通过观察视觉刺激器上的左右手连续播放图像刺激产生脑电信号，采用带通滤波提高信噪比，用滑动窗截取脑电数据并且对截取的数据从能量的角度分析得到运动想象特征，同时可以在线提取特征，为实现实时系统打下了基础。 结果与结论：该方案能有效地提取出运动想象特征，并且通过离线模式识别进行了有效的分类，分类效果达到了82%。

A system of motor imaging brain-computer interface based on LabVIEW

BACKGROUND: The brain-computer interface (BCI) based on event-related potential can be widely used in the rehabilitation of disabled patients, showing its importance and the feasibility of future implementation. OBJECTIVE: To present the realization of BCI based on motor imaging under LabVIEW. METHODS: The critical parts of the solution are the realization of the visual stimulation and the feature extraction of electroencephalogram (EEG). The testee fixates on playback images of the left and right hand on the screen, which can induce EEG. The band pass filtering is used to improve the signal-to-noise ratio (SNR). The EEG data intercepted with the sliding window have been analyzed from the perspective of time-domain energy and obtained the feature extraction of motor imaging EEG. On-line feature extraction lays the foundation for the realization of real-time system. RESULTS AND CONCLUSION: The program can effectively extract the features of motor imagery, and effectively conduct a classification by off-line pattern recognition, with classification results achieving 82%.