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Springer, Berlin, Heidelberg

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10.1002/jat.3424

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Online Emotion Classification from Electroencephal

Authors: Thierry Castermans Matthieu Duvinage Nicolas Riche
Publish Date: 2013/6/9
Volume: , Issue: , Pages: 251-262
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Abstract

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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