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发表刊物：JOURNAL OF NEURAL ENGINEERING

摘要：In this study, a novel method of phase constrained canonical correlation analysis (p-CCA) is presented for classifying steady-state visual evoked potentials (SSVEPs) using multichannel electroencephalography (EEG) signals. p-CCA is employed to improve the performance of the SSVEP-based brain–computer interface (BCI) system using standard CCA. SSVEP response phases are estimated based on the physiologically meaningful apparent latency and are added as a reliable constraint into standard CCA. The results of EEG experiments involving 10 subjects demonstrate that p-CCA consistently outperforms standard CCA in classification ccuracy. The improvement is up to 6.8% using 1–4 s data segments. The results indicate that the reliable measurement of phase information is of importance in SSVEP-based BCIs.

论文类型：期刊论文

是否译文：否

发表时间：2011-05-13

收录刊物：SCI

DOI码：10.1088/1741-2560/8/3/036027

第一作者：潘洁

合写作者：高小榕,段放,闫铮

通讯作者：高上凯