首页> 外文会议>Neural Engineering, 2009. NER '09 >Combination of independent component analysis and feature extraction of ERP for level classification of sustained attention
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Combination of independent component analysis and feature extraction of ERP for level classification of sustained attention

机译:独立成分分析与ERP的特征提取相结合的持续关注水平分类

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This paper investigates the relations between ERP features and visual sustained attention. Continuous Performance Test is used for determining sustained attention level. Fifty eight features were extracted from the 19-channel recorded signals. Twenty four subjects were divided into three classes according to their attention level. LDA classifier is used and high accuracy (94%, 88% and 93% for each two classes) is achieved by using two features in classifying the test data. Obtained results are in agreement with the previous studies.
机译:本文研究了ERP功能与视觉持续注意力之间的关系。连续性能测试用于确定持续关注水平。从19通道记录的信号中提取了58个特征。根据他们的注意力水平,将二十四名受试者分为三类。使用LDA分类器,通过使用两个功能对测试数据进行分类,可以实现较高的准确性(每两个类别分别为94%,88%和93%)。获得的结果与以前的研究一致。

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