基于稳态视觉诱发电位和注意力脑电的混合脑机接口系统  

Hybrid Brain-computer Interface System Based on SSVEP and Attention EEG

作　　者：刘志民 姜旭 化建宁 LIU Zhimin;JIANG Xu;HUA Jianning(Institute of Control Engineering,Northeast University at Qinhuangdao,Qinhuangdao 066004,China)

机构地区：[1]东北大学秦皇岛分校控制工程学院,河北秦皇岛066004

出　　处：《信息与控制》2021年第6期748-753,760,共7页Information and Control

摘　　要：针对注意力脑电信号的多分类研究、脑机接口系统的实验范式扩展等问题,设计了一种基于稳态视觉诱发电位(SSVEP)和注意力脑电的混合脑机接口系统.首先,对注意力脑电的多级分类进行探索,设计了融合空间注意和脑力任务的注意力范式,改善注意力脑电的分类性能.脑机接口实验中,使用α波阻断信号实现SSVEP和注意力诱发界面的切换;SSVEP信号用于控制机器人的运动;注意力分级用于改变机器人的运动速度.实验招募了10名被试进行脑机接口系统的实验,实验结果显示,注意力信号的三分类正确率达78.2%;被试控制机器人到达目标位置的正确率可达100%.A hybrid brain-computer interface(BCI)system based on SSVEP and attention EEG is designed,for the problems of multi-classification for attention EEG and the expansion of the experimental paradigm of the BCI system.Firstly,the multi-classification of attention EEG is explored,and an attentional paradigm that integrates spatial attention and mental tasks is designed to improve the classification performance of attention EEG.In the brain-controlled robot experiment,theα-block signal is used to switch SSVEP and attentional stimulation interface.SSVEP signal is used to control the movement of the robot.Attention EEG is used to change the speed of the robot moves.Ten subjects are recruited to experiment with the brain-computer interface system.The results show that the accuracy of three-classification of attention signals reach 78.2%.The correct rate of the robot reaching the target position can get to 100%.

关 键 词：脑机接口 稳态视觉诱发电位 注意力脑电 α波阻断 机器人 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]