Single trial classification of EEG and peripheral physiological signals for recognition of emotions induced by music videos

Sander Koelstra, Ashkan Yazdani, Mohammad Soleymani, Christian Mühl, Jong Seok Lee, Anton Nijholt, Thierry Pun, Touradj Ebrahimi, Ioannis Patras

Research output: Chapter in Book/Report/Conference proceedingConference contribution

90 Citations (Scopus)

Abstract

Recently, the field of automatic recognition of users' affective states has gained a great deal of attention. Automatic, implicit recognition of affective states has many applications, ranging from personalized content recommendation to automatic tutoring systems. In this work, we present some promising results of our research in classification of emotions induced by watching music videos. We show robust correlations between users' self-assessments of arousal and valence and the frequency powers of their EEG activity. We present methods for single trial classification using both EEG and peripheral physiological signals. For EEG, an average (maximum) classification rate of 55.7% (67.0%) for arousal and 58.8% (76.0%) for valence was obtained. For peripheral physiological signals, the results were 58.9% (85.5%) for arousal and 54.2% (78.5%) for valence.

Original languageEnglish
Title of host publicationBrain Informatics - International Conference, BI 2010, Proceedings
Pages89-100
Number of pages12
DOIs
Publication statusPublished - 2010 Nov 19
Event2010 International Conference on Brain Informatics, BI 2010 - Toronto, ON, Canada
Duration: 2010 Aug 282010 Aug 30

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6334 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other2010 International Conference on Brain Informatics, BI 2010
CountryCanada
CityToronto, ON
Period10/8/2810/8/30

Fingerprint

Electroencephalography
Music
Self-assessment
Recommendations
Emotion
Electroencephalogram

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Koelstra, S., Yazdani, A., Soleymani, M., Mühl, C., Lee, J. S., Nijholt, A., ... Patras, I. (2010). Single trial classification of EEG and peripheral physiological signals for recognition of emotions induced by music videos. In Brain Informatics - International Conference, BI 2010, Proceedings (pp. 89-100). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6334 LNAI). https://doi.org/10.1007/978-3-642-15314-3_9
Koelstra, Sander ; Yazdani, Ashkan ; Soleymani, Mohammad ; Mühl, Christian ; Lee, Jong Seok ; Nijholt, Anton ; Pun, Thierry ; Ebrahimi, Touradj ; Patras, Ioannis. / Single trial classification of EEG and peripheral physiological signals for recognition of emotions induced by music videos. Brain Informatics - International Conference, BI 2010, Proceedings. 2010. pp. 89-100 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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abstract = "Recently, the field of automatic recognition of users' affective states has gained a great deal of attention. Automatic, implicit recognition of affective states has many applications, ranging from personalized content recommendation to automatic tutoring systems. In this work, we present some promising results of our research in classification of emotions induced by watching music videos. We show robust correlations between users' self-assessments of arousal and valence and the frequency powers of their EEG activity. We present methods for single trial classification using both EEG and peripheral physiological signals. For EEG, an average (maximum) classification rate of 55.7{\%} (67.0{\%}) for arousal and 58.8{\%} (76.0{\%}) for valence was obtained. For peripheral physiological signals, the results were 58.9{\%} (85.5{\%}) for arousal and 54.2{\%} (78.5{\%}) for valence.",
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Koelstra, S, Yazdani, A, Soleymani, M, Mühl, C, Lee, JS, Nijholt, A, Pun, T, Ebrahimi, T & Patras, I 2010, Single trial classification of EEG and peripheral physiological signals for recognition of emotions induced by music videos. in Brain Informatics - International Conference, BI 2010, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6334 LNAI, pp. 89-100, 2010 International Conference on Brain Informatics, BI 2010, Toronto, ON, Canada, 10/8/28. https://doi.org/10.1007/978-3-642-15314-3_9

Single trial classification of EEG and peripheral physiological signals for recognition of emotions induced by music videos. / Koelstra, Sander; Yazdani, Ashkan; Soleymani, Mohammad; Mühl, Christian; Lee, Jong Seok; Nijholt, Anton; Pun, Thierry; Ebrahimi, Touradj; Patras, Ioannis.

Brain Informatics - International Conference, BI 2010, Proceedings. 2010. p. 89-100 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6334 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Koelstra S, Yazdani A, Soleymani M, Mühl C, Lee JS, Nijholt A et al. Single trial classification of EEG and peripheral physiological signals for recognition of emotions induced by music videos. In Brain Informatics - International Conference, BI 2010, Proceedings. 2010. p. 89-100. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-15314-3_9