Classification of Emotion Primitives from EEG Signals Using Visual and Audio Stimuli

被引：0

作者：

Dasdemir, Yasar ^{[1
]}

Yildirim, Serdar ^{[2
]}

Yildirim, Esen ^{[2
]}

机构：

[1] Mustafa Kemal Univ, Enformat, Antakya, Turkey

[2] Mustafa Kemal Univ, Bilgisayar Muhendisligi, Antakya, Turkey

来源：

2015 23RD SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2015年

关键词：

EEG; Arousal; Valence; Emotion Primitive Classification;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Emotion recognition from EEG signals has an important role in designing Brain-Computer Interface. This paper compares effects of audio and visual stimuli, used for collecting emotional EEG signals, on emotion classification performance. For this purpose EEG data from 25 subjects are collected and binary classification (low/high) for valence and activation emotion dimensions are performed. Wavelet transform is used for feature extraction and 3 classifiers are used for classification. True positive rates of 71.7% and 78.5% are obtained using audio and video stimuli for valence dimension 71% and 82% are obtained using audio and video stimuli for arousal dimension, respectively.

引用

页码：2250 / 2253

页数：4

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