Research of steady-state visual evoked potential based online brain-computer interface

doi:10.3778/j.issn.1002-8331.1504-0257

Abstract

Abstract: 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 employing the portable EEG collecting device Emotiv EPOC and the NAO robot, which has a good ability of anti-noise. This system utilizes 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 of 4 types of tasks achieves 87. 50%. The online experiment doesn’t suffer from the surrounding noise, which shows the system has a good ability to resist the noise.

Key words: steady-state visual evoked potential, brain computer interface, Emotiv EPOC, NAO robot, canonical correlation analysis

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Emotiv EPOC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。

关键词: 稳态视觉诱发电位, 脑机接口, Emotiv EPOC, NAO机器人, 典型相关性分析

DONG Enzeng, GUO Guangrui, CHEN Chao. Research of steady-state visual evoked potential based online brain-computer interface[J]. Computer Engineering and Applications, 2017, 53(3): 154-159.

董恩增，郭光瑞，陈超. 基于稳态视觉诱发电位的在线脑机接口研究[J]. 计算机工程与应用, 2017, 53(3): 154-159.

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Research of steady-state visual evoked potential based online brain-computer interface

基于稳态视觉诱发电位的在线脑机接口研究

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