{"title":"A half-field stimulation pattern for SSVEP-based brain-computer interface.","authors":"Zheng Yan,&nbsp;Xiaorong Gao,&nbsp;Guangyu Bin,&nbsp;Bo Hong,&nbsp;Shangkai Gao","doi":"10.1109/IEMBS.2009.5333544","DOIUrl":null,"url":null,"abstract":"<p><p>A novel stimulation pattern has been designed for brain-computer interface (BCI) using steady-state visual evoked potential (SSVEP) signals. Each target is composed of two flickers placed on right-and-left visual fields. The user is expected to concentrate his or her sight on the fixation point which is located in the middle of the two flickers modulated at specific frequencies respectively. Considering the role of optic chiasm, the two frequency components could be extracted from contralateral occipital regions. Canonical correlation analysis (CCA) was applied to distinguish the electroencephalography (EEG) frequency components from right-and-left visual cortex. The attractive feature of this method is that it would substantially increase the number of targets by a combination of frequencies. Based on this technique a nine-target SSVEP-based BCI system was designed using only three different frequencies. The test results with 8 subjects showed a classification accuracy between 40.0% and 96.3%.</p>","PeriodicalId":72237,"journal":{"name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","volume":" ","pages":"6461-4"},"PeriodicalIF":0.0000,"publicationDate":"2009-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/IEMBS.2009.5333544","citationCount":"26","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMBS.2009.5333544","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 26

Abstract

A novel stimulation pattern has been designed for brain-computer interface (BCI) using steady-state visual evoked potential (SSVEP) signals. Each target is composed of two flickers placed on right-and-left visual fields. The user is expected to concentrate his or her sight on the fixation point which is located in the middle of the two flickers modulated at specific frequencies respectively. Considering the role of optic chiasm, the two frequency components could be extracted from contralateral occipital regions. Canonical correlation analysis (CCA) was applied to distinguish the electroencephalography (EEG) frequency components from right-and-left visual cortex. The attractive feature of this method is that it would substantially increase the number of targets by a combination of frequencies. Based on this technique a nine-target SSVEP-based BCI system was designed using only three different frequencies. The test results with 8 subjects showed a classification accuracy between 40.0% and 96.3%.

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基于ssvep的脑机接口半场刺激模式。
设计了一种基于稳态视觉诱发电位(SSVEP)信号的脑机接口(BCI)刺激模式。每个目标由放置在左右视野上的两个闪烁组成。期望用户将其视线集中在分别以特定频率调制的两个闪烁中间的注视点上。考虑到视交叉的作用,可以从对侧枕区提取两个频率分量。应用典型相关分析(Canonical correlation analysis, CCA)区分左右视皮层的脑电图(EEG)频率成分。这种方法吸引人的特点是,它可以通过频率组合大大增加目标的数量。基于该技术,设计了一种仅使用三个不同频率的九目标ssvep - BCI系统。8个被试的分类准确率在40.0% ~ 96.3%之间。
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