首页> 外文会议>Industrial Electronics, 2009. IECON '09 >A study on relationship between personal feature of EEG and human's characteristic for BCI based on mental state
【24h】

A study on relationship between personal feature of EEG and human's characteristic for BCI based on mental state

机译:基于精神状态的脑电图人格特征与BCI人格特征的关系研究

获取原文

摘要

This paper discusses the relationship the result classified the electroencephalogram (EEG) patterns while listening to music and the human's nature, which indicates the personal feature of a human, based on the egogram pattern. The EEG analysis calculates the power spectra of the frequency of the EEG signal, divides into the frequency bands based on theta, alpha, and beta rhythms, and evaluates whether the music matches mood of the user or not through EEG pattern classification. A k-nearest neighbor classifier is used to classify the EEG patterns. The egogram is used for detecting nature of the human. Finally, we discuss the relationship the result of EEG pattern classification and the human's nature. An interesting finding was that the recognition accuracy of the EEG pattern meaning the response of them on negative stimuli became high when the subject was classified into the egogram pattern with introverted nature.
机译:本文讨论了根据心电图模式将听音乐时脑电图(EEG)模式分类与人的自然特征之间的关系,这表明人的个人特征。脑电图分析计算脑电图信号频率的功率谱,根据θ,α和β节奏将其划分为频带,并通过脑电图模式分类来评估音乐是否与用户的情绪匹配。 k最近邻分类器用于对EEG模式进行分类。该egogram用于检测人的本性。最后,我们讨论了脑电模式分类结果与人的天性之间的关系。一个有趣的发现是,当将对象分类为具有内向性的egogram模式时,EEG模式的识别准确性(意味着它们对负刺激的响应)变得很高。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号