Feature extraction of SSVEP-based brain-computer interface with ICA and HHT method - 文章详情页

作者：

Ruan, Xiaogang (Ruan, Xiaogang.) | Xue, Kun (Xue, Kun.) | Li, Mingai (Li, Mingai.) (学者：李明爱)

收录：

EI Scopus

摘要：

For　the　problem　of　extracting　feature　of　steady-state　visual　evoked　potential　(SSVEP)-based　brain-computer　interface　(BCI)　system　efficiently,　a　method　based　on　independent　component　analysis　(ICA)　and　Hilbert-Huang　transform　(HHT)　is　proposed　in　this　paper.　Firstly,　Band-pass　filter　is　applied　to　preprocess　the　electroencephalograph　(EEG)　of　SSVEP.　Secondly,　the　independent　components　are　acquired　from　filtered　signals　with　ICA.　Thirdly,　HHT　is　applied　to　decompose　the　independent　components　to　obtain　the　intrinsic　mode　function　(IMF)　needed.　Finally,　frequency　domain　analysis　is　applied　to　analyse　IMF.　The　experiments　show　that　the　proposed　method　is　feasible　in　feature　extraction　and　the　noise　can　be　removed.　©　2014　IEEE.

关键词：

Bandpass filters Biomedical signal processing Brain computer interface Electroencephalography Extraction Feature extraction Frequency domain analysis Independent component analysis Intelligent control Interfaces (computer) Interface states Mathematical transformations

作者机构：

[ 1 ] [Ruan, Xiaogang]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing; 100022, China
[ 2 ] [Xue, Kun]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing; 100022, China
[ 3 ] [Li, Mingai]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing; 100022, China

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