Emotion recognition of EEG underlying favourite music by support vector machine

Kevin C. Tseng, Bor-Shyh Lin, Chang Mu Han, Psi Shi Wang

研究成果: Conference contribution同行評審

21 引文 斯高帕斯(Scopus)

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.

原文English
主出版物標題ICOT 2013 - 1st International Conference on Orange Technologies
頁面155-158
頁數4
DOIs
出版狀態Published - 12 七月 2013
事件1st International Conference on Orange Technologies, ICOT 2013 - Tainan, Taiwan
持續時間: 12 三月 201316 三月 2013

出版系列

名字ICOT 2013 - 1st International Conference on Orange Technologies

Conference

Conference1st International Conference on Orange Technologies, ICOT 2013
國家Taiwan
城市Tainan
期間12/03/1316/03/13

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