【摘要】 为揭示疑犯隐藏的真实信息,检测隐秘信息的脑电,设计了一个猜测受试者真实名字.结果表明:在个体对不同自我相关程度名字产生刺激,在刺激出现后的300～600 ms内,本人名字诱发的正波幅值大于陌生名字刺激.通过小波变换提取特征,用支持向量机进行训练和分类.在进行5个试次叠加平均后,采用PO3通道可将自己的名字分类成功,5位被试平均正确率达98%,该方法可应用于个体隐秘信息的脑电检测.更多还原

【Abstract】 To uncover the hidden information of suspects,electroencephalogram( EEG) containing secret information was measured. An experiment to find the real names of the subjects was designed. It was found that the individuals were stimulated by self-relevant names with different degrees. The amplitude of positive wave induced by one’s own name was larger than the other names during the 300—600 ms after the stimulation. The feature points were extracted by wavelet transform,then trained and classified by support vector machine. After 5 trials of superposition averaging,the average accuracy of 5 subjects could reach 98% by using PO3 channel to classify their own names. This method could be applied to EEG detection of individual hidden information.更多还原