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Online Emotion Classification from Electroencephalographic Signals: A First Study Conducted in a Realistic Movie Theater

Authors: Thierry Castermans, Matthieu Duvinage, Nicolas Riche,

Publish Date: 2013/6/9
Volume: , Issue:, Pages: 251-262
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New affordable electroencephalographic (EEG) devices dedicated to the game industry have recently appeared on the market. Consequently, more and more artists inspired by these promising technologies imagine the possibility to directly integrate human emotions in their performance through measurement of the brain waves. In this paper, we describe a first attempt to detect the valence (positive or negative value) of emotions provoked by different video excerpts amongst several spectators seated in a realistic movie theater, on the basis of their EEG signals only. Preliminary results obtained with consumer grade EEG headsets indicate that positively and negatively valenced video excerpts may be discriminated in the training data set but not on an independent data set. These results are extensively discussed as well as further studies and developments that should be made to improve performance in the future.



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