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Association between ego scores and individual characteristics in EEG analysis: Basic study on individual brain activity

机译:EEG分析中自我评分与个体特征之间的关联:个体脑活动的基础研究

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This paper introduces a method for discussing an association between ego scores and individual characteristics in EEG analysis. The ego scores express one of the personality and/or nature on a human. The EEG analysis calculates the power spectra of the frequency weighted of the EEG signal, and evaluates through detecting the EEG patterns while listening to the music. A k-nearest neighbor classifier is used to detect the EEG patterns. The specified weight value to weight frequency of EEG and the results of EEG pattern detection express the individual characteristics in EEG analysis. Finally, we do experiment using a real EEG data for discussing the association the ego scores and the individual characteristics in EEG analysis. An interesting tendency was that the subjects who were the combined ego-type tended to have a powerful response to negative stimuli more than positive stimuli. They had the stable filter weighted frequency.
机译:本文介绍了一种讨论自我评分与脑电图分析中的个体特征之间的关联的方法。自我评分表达人类的一个人格和/或性质。 EEG分析计算EEG信号的频率加权的功率谱,并通过在收听音乐时检测EEG模式来评估。 k最近邻分类器用于检测EEG模式。 EEG的指定权重值和EEG模式检测结果表达了EEG分析中的个体特征。最后,我们使用真正的EEG数据进行实验,以讨论协会的自我评分和脑电图分析中的个体特征。一个有趣的趋势是,综合自我型的受试者倾向于对负刺激的强烈反应而不是积极的刺激。它们具有稳定的滤波器加权频率。

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