中文摘要：

针对脑机接口中存在的抗噪声能力差、操作复杂的问题，利用便携式脑电采集设备EmotivEPOC以及NAO机器人，搭建了一个抗噪能力较好的稳态视觉诱发在线脑机接口系统。该系统采用典型相关性分析进行稳态视觉诱发电位的频率识别。在线实验中受试者通过Emotiv控制NAO机器人运动，四类任务的准确率达到87.50%。在线实验没有回避周围的噪声，表明该系统具有较好的抗噪能力。

英文摘要：

The most brain-computer interface systems perform badly in resisting the noise and seem complicated for operation.This paper proposes a steady-state visual evoked potential based online brain computer interface system employingthe portable EEG collecting device Emotiv EPOC and the NAO robot,which has a good ability of anti-noise.This systemutilizes canonical correlation analysis to detect the frequency of steady-state visual evoked potential.In online experiment,the NAO robot is controlled by the EEG signals collected from Emotiv EPOC,the average classification accuracy rate of4types of tasks achieves87.50%.The online experiment doesn’t suffer from the surrounding noise,which shows the systemhas a good ability to resist the noise.