计算机与数字工程2017，Vol.45Issue(5)：923-928,6.DOI:10.3969/j.issn.1672-9722.2017.05.028
"模拟阅读"脑-机接口N2P3成分的自动提取
Automatic Extraction of N2 and P3 in Imitating-Reading BCI
摘要
Abstract
This paper introduces a method of single automatically extract EEG of N2 and P3 component based on ICA and big?gest local energy. Experiment collectes seven healthy people 32 lead EEG in the state of observed at"Imitating-Reading"stimula?tion interface. Firstly,single trial EEG is taken into blind source separation using the FastICA algorithm to 32 component result. Sec?ondly,automatic extraction N2 and P3 components in the 32 component result at the fixed time period,using maximum sample vari?ance method. The N2,P3 component directly are as a single extraction feature and SVM classification method is used to classify,at the same time compared with the classification that using characteristics parameters of best single-channel in the time-domain. The results indicate that using automatic extraction of a single EEG N2 and P3 component based on ICA method is effective and classifi?cation results has risen considerably than the best single channel.关键词
模拟阅读/ICA/单次特征/自动提取/SVMKey words
imitating-reading/ICA/single feature/automatic extraction/SVM分类
信息技术与安全科学引用本文复制引用
金震,官金安,赵瑞娟,谢国栋.."模拟阅读"脑-机接口N2P3成分的自动提取[J].计算机与数字工程,2017,45(5):923-928,6.基金项目
国家自然科学基金资助项目(编号:91120017,81271659) （编号:91120017,81271659）
中央高校基本科研业务费资助项目(编号:CZY13031)资助. （编号:CZY13031）
