Improving BCI-based emotion recognition by combining EEG feature selection and kernel classifiers
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- 作者：John Atkinson ; a ; atkinson@inf.udec.cl" class="auth_mail" title="E-mail the corresponding author ; Daniel Camposb ; dancamposf@inf.udec.cl" class="auth_mail" title="E-mail the corresponding author
- 关键词：Emotion recognition ; Brain&ndash ; Computer Interfaces ; EEG ; Feature selection ; Emotion classification
- 刊名：Expert Systems with Applications
- 出版年：2016
- 出版时间：1 April 2016
- 年：2016
- 卷：47
- 期：Complete
- 页码：35-41
- 全文大小：1138 K
文摘
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A feature-based emotion recognition model is proposed for EEG-based BCI.
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The approach combines statistical-based feature selection methods and SVM emotion classifiers.
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The model is based on Valence/Arousal dimensions for emotion classification.
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Our combined approach outperformed other recognition methods.