Adaptive Active Auditory Brain Computer Interface

被引：4

作者：

Hong, Bo ^{[1
]}

Lou, Bin ^{[1
]}

Guo, Jing ^{[1
]}

Gao, Shangkai ^{[1
]}

机构：

[1] Tsinghua Univ, Dept Biomed Engn, Beijing 100084, Peoples R China

来源：

2009 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-20 | 2009年

关键词：

brain computer interface; auditory; adaptive; support vector machine; late positive component; P300; SPELLER; POTENTIALS; BCI;

D O I：

10.1109/IEMBS.2009.5334133

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

An active paradigm was employed to produce reliable and prominent target response in an auditory brain computer interface (BCI), in which subject's voluntary recognition of the property of a target human voice enhances the discriminability between target and non-target EEG response. Furthermore, to adaptively decide the optimal number of trials being averaged for SVM classification, a statistical approach was proposed to convert each sample's margin in support vector space into probabilities of each voice choice being the target. In a testing of 8 subjects' EEG data from the active auditory BCI experiment, the proposed adaptive approach needs only about 4-6 trials to reach the equivalent accuracy of 15-trial averaging. The improved information transfer rate suggests the advantage of adaptive strategy in an active auditory BCI.

引用

页码：4531 / 4534

页数：4

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