Eeg-based emotion recogntion during emotionally evocative films

It is difficult to classify anger, fear, and surprise emotions with autonomic nervous system response patterns, because these three emotions show similar levels of valence and arousal dimensions. The purpose of this study was to classify three emotions by using EEG signals. Linear discriminant analy...

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Bibliographic Details
Main Authors: Mi-Sook Park, Hyeong-Seok Oh, Hoyeon Jeong, Jin-Hun Sohn
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
brain coherence
Coherence
EEG
EEG asymmetry
Electrodes
Electroencephalography
emotion
Emotion recognition
Feature extraction
Citations: Items that cite this one
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Summary:It is difficult to classify anger, fear, and surprise emotions with autonomic nervous system response patterns, because these three emotions show similar levels of valence and arousal dimensions. The purpose of this study was to classify three emotions by using EEG signals. Linear discriminant analysis (LDA) using three types of EEG characteristics showed that the mean recognition accuracy was 66.3%. These findings reveal that three emotions were successfully able to be classified based on EEG signals.
DOI:10.1109/IWW-BCI.2013.6506629