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基于支持向量机的BCI导联选择算法 被引量:2

The BCI Channel Selection Algorithm Based on SVM
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摘要 脑-机接口(BCI)中导联选择的目的是在所有记录脑电信号的导联中,选择出与特定心理任务分类最相关的导联,对于简化BCI系统,提高系统传输速率具有重要影响。本研究提出一种基于支持向量机(SVM)的导联选择算法,所采用的实验数据来自德国组织的第三届国际BCI数据竞赛数据集IVa中两个受试者(al,aw)。结果表明,该算法对al数据集导联可从118减少到22,同时系统识别的精度从92%提高到98%;对aw数据集导联可从118减少到35,同时系统识别的精度从89%提高到93%。可简化BCI系统的设计,改善系统性能。
作者 张胜 王蔚
出处 《中国生物医学工程学报》 CAS CSCD 北大核心 2009年第4期624-627,共4页 Chinese Journal of Biomedical Engineering
基金 浙江省自然科学基金(Y207738) 全国教育科学"十五"重点项目(DCA050056)
关键词 脑-机接口 导联选择 支持向量机(SVM) 特征选择 brain-computer interface channel selection support vector machine (SVM) feature selection
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参考文献8

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二级参考文献1

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同被引文献16

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