Eeg-based emotion recogntion during emotionally evocative films

Author

Mi-Sook Park ; Hyeong-Seok Oh ; Hoyeon Jeong ; Jin-Hun Sohn

Author_Institution

Dept. of Psychol., Chungnam Nat. Univ., Daejeon, South Korea

fYear

2013

fDate

18-20 Feb. 2013

Firstpage

56

Lastpage

57

Abstract

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.

Keywords

electroencephalography; emotion recognition; medical signal processing; signal classification; EEG characteristics; EEG signals; EEG-based emotion recognition; LDA; anger emotion; arousal dimensions; autonomic nervous system response patterns; emotion classification; emotionally evocative film; fear emotion; linear discriminant analysis; mean recognition accuracy; surprise emotions; valence; Accuracy; Coherence; Electrodes; Electroencephalography; Emotion recognition; Feature extraction; Films; EEG; EEG asymmetry; brain coherence; emotion;

fLanguage

English

Publisher

ieee

Conference_Titel

Brain-Computer Interface (BCI), 2013 International Winter Workshop on

Conference_Location

Gangwo

Print_ISBN

978-1-4673-5973-3

Type

conf

DOI

10.1109/IWW-BCI.2013.6506629

Filename

6506629