Abstract
Studying emotions has become increasingly popular in various research fields. Researchers across the globe have studied various tools to implicitly assess emotions and affective states of people. Human computer interface systems specifically can benefit from such implicit emotion evaluator module, which can help them determine their users’ affective states and act accordingly. Brain electrical activity can be considered as an appropriate candidate for extracting emotion-related cues, but it is still in its infancy. In this paper, the results of analyzing the Electroencephalogram (EEG) for assessing emotions elicited during watching various pre-selected emotional music video clips have been reported. More precisely, in-depth results of both subject-dependent and subject-independent correlation analysis between time domain, and frequency domain features of EEG signal and subjects’ self assessed emotions are produced and discussed.
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Kroupi, E., Yazdani, A., Ebrahimi, T. (2011). EEG Correlates of Different Emotional States Elicited during Watching Music Videos. In: D’Mello, S., Graesser, A., Schuller, B., Martin, JC. (eds) Affective Computing and Intelligent Interaction. ACII 2011. Lecture Notes in Computer Science, vol 6975. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24571-8_58
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DOI: https://doi.org/10.1007/978-3-642-24571-8_58
Publisher Name: Springer, Berlin, Heidelberg
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