Single Trial Classification of EEG and Peripheral Physiological Signals for Recognition of Emotions Induced by Music Videos

S. Koelstra, A. Yazdani, M. Soleymani, C. Mühl, J.-L. Lee, Antinus Nijholt, T. Pun, T. Ebrahimi, I. Patras

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    144 Citations (Scopus)


    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 languageUndefined
    Title of host publicationProceedings 2010 International Conference on Brain Informatics (BI 2010)
    EditorsY. Yao, R. Sun, T. Poggio, J. Liu, N. Zhong, J. Huang
    Place of PublicationBerlin
    Number of pages12
    ISBN (Print)978-3-642-15313-6
    Publication statusPublished - 4 Sep 2010
    EventProceedings 2010 International Conference on Brain Informatics (BI 2010), Toronto: Proceedings 2010 International Conference on Brain Informatics (BI 2010) - Berlin
    Duration: 4 Sep 2010 → …

    Publication series

    NameLecture Notes in Computer Science
    PublisherSpringer Verlag
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    ConferenceProceedings 2010 International Conference on Brain Informatics (BI 2010), Toronto
    Period4/09/10 → …


    • METIS-271010
    • MUSIC
    • Affective Computing
    • IR-73064
    • EWI-18368
    • EEG
    • Emotion induction
    • Physiological Signals

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