摘要
在非植入式脑-机接口(BCI)研究中,独立分量分析(ICA)一直被认为是具有很大应用前景的脑电(EEG)预处理和特征增强方法,但到目前为止,有关在线ICA-BCI系统的研究与实现的报道还不多见。本文对基于ICA的运动想象BCI(MIBCI)系统进行研究,结合ICA无监督学习特点和运动相关去同步化(ERD)现象,构建了一种简单实用的ICA空域滤波器设计方法和三类运动想象判别准则。为了验证所提算法的在线处理性能,本文基于Neuro Scan脑电采集系统和VC++软件平台,完整地实现了在线ICA-MIBCI实验系统。4名受试者参加了系统测试实验,其中两名受试者参加了在线模式的实验。离线和在线实验的三分类运动想象识别结果分别达到了89.78%和89.89%。实验结果表明,本文所提算法分类正确率高,时间开销小,具备跨平台移植的潜力。
In the research of non-invasive brain-computer interface （BCI）, independent component analysis （ICA） has been considered as a promising method of electroencephalogram （EEG） preprocessing and feature enhancement. However, there have been few investigations and implements about online ICA-BCI system up till now. This paper reports the investigation of the ICA-based motor imagery BCI （MIBCI） system, combining the characteristics of unsupervised learning of ICA and event-related desynchronization （ERD） related to motor imagery. We constructed a simple and practical method of ICA spatial filter calculation and discriminate criterion of three-type motor imageries in the study. To validate the online performance of proposed algorithms, an ICA-MIBCI experimental system was fully established based on NeuroScan EEG amplifier and VC＋＋ platform. Four subjects participated in the experiment of MIBCI testing and two of them took part in the online experiment. The average classification accuracies of the three-type motor imageries reached 89.78% and 89.89% in the offiine and online testing, respectively. The experimental results showed that the proposed algorithm produced high classification accuracy and required less time consumption, which would have a prospect of cross platform application.
作者
胡盼
张磊
周蚌艳
吴小培
HU Pan ZHANG Lei ZHOU Bangyan WU Xiaopei(School of Computer Science and Technology, Anhui University, Hefei 230601, P.R.China The Key Lab. of Intelligent Computing and Signal Processing, Ministry of Education, Anhui University, Hefei 230039, P.R.China)
出处
《生物医学工程学杂志》
EI
CAS
CSCD
北大核心
2017年第1期106-114,共9页
Journal of Biomedical Engineering
基金
国家自然科学基金(61271352
61401002)
关键词
独立分量分析
脑-机接口
在线系统
运动想象
independent component analysis
brain-computer interface
online system
motor imagery
