首页> 外文会议>1st International Conference on Orange Technologies >Emotion recognition of EEG underlying favourite music by support vector machine
【24h】

Emotion recognition of EEG underlying favourite music by support vector machine

机译:支持向量机对喜欢的音乐基础的脑电信号的情感识别

获取原文
获取原文并翻译 | 示例

摘要

This study aims to research the relationship between electroencephalography (EEG) at the prefrontal cortex (PFC) and emotion in the condition of different preference levels of music by applying a support vector machine (SVM). To achieve this, this study presents an EEG-based brain computer interface (BCI) music player, which can simultaneously analyse brain activities in real time and objectively provide therapists with physiological data for emotion detection in the experiment. The SVM result shows that more than 80% accuracy of elicited emotion based on 28 participants was analysed under the two factors of the frontal midline theta and alpha relation ratio. As such, it might suggest that significantly different stimuli are capable of enticing discernible EEG responses at frontal lobes, which is an indication of emotion and of providing an effective approach for application to multimedia with the abilities of EEG interpretation.
机译:本研究旨在通过应用支持向量机(SVM)研究在音乐的不同喜好级别下前额叶皮层(PFC)的脑电图(EEG)与情绪之间的关系。为了实现这一目标,本研究提出了一种基于EEG的脑部计算机接口(BCI)音乐播放器,该播放器可以同时实时分析脑部活动,并客观地为治疗师提供用于实验中情绪检测的生理数据。 SVM结果显示,在额中线theta和alpha关系比率这两个因素的基础上,分析了基于28位参与者的超过80%的引起情绪的准确性。因此,这可能表明明显不同的刺激能够诱使额叶处可辨别的EEG反应,这表示情绪,并为具有EEG解释能力的多媒体应用提供了有效的方法。

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