DEAP : a Database for Emotion Analysis Using Physiological Signals

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

doi:10.1109/T-AFFC.2011.15

Scientific article

English

DEAP : a Database for Emotion Analysis Using Physiological Signals

Contributors

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

Published in

IEEE transactions on affective computing, vol. 3, no. 1, p. 18-31

Publication date

2012

Abstract

We present a multimodal data set for the analysis of human affective states. The electroencephalogram (EEG) and peripheral physiological signals of 32 participants were recorded as each watched 40 one-minute long excerpts of music videos. Participants rated each video in terms of the levels of arousal, valence, like/dislike, dominance, and familiarity. For 22 of the 32 participants, frontal face video was also recorded. A novel method for stimuli selection is proposed using retrieval by affective tags from the last.fm website, video highlight detection, and an online assessment tool. An extensive analysis of the participants' ratings during the experiment is presented. Correlates between the EEG signal frequencies and the participants' ratings are investigated. Methods and results are presented for single-trial classification of arousal, valence, and like/dislike ratings using the modalities of EEG, peripheral physiological signals, and multimedia content analysis. Finally, decision fusion of the classification results from different modalities is performed. The data set is made publicly available and we encourage other researchers to use it for testing their own affective state estimation methods.

Keywords

Web sites
Electroencephalography
Emotion recognition
Image classification
Information retrieval
Multimedia computing
Neurophysiology
State estimation
Video signal processing
DEAP
EEG signal frequencies
Web site
Arousal
Decision fusion
Dominance
Electroencephalogram
Emotion analysis
Familiarity
Frontal face video
Human affective states
Multimedia content analysis
Multimodal data set
Music videos
Online assessment tool
Peripheral physiological signals
Single-trial classification
State estimation methods
Stimuli selection
Video highlight detection
Databases
Face
Motion pictures
Multimedia communication
Videos
Visualization
EEG
Emotion classification
Affective computing.
Pattern classification
Physiological signals
Signal processing

UNIGE affiliation entities

UNIGE research groups

Citation (ISO format)

KOELSTRA, Sander et al. DEAP : a Database for Emotion Analysis Using Physiological Signals. In: IEEE transactions on affective computing, 2012, vol. 3, n° 1, p. 18–31. doi: 10.1109/T-AFFC.2011.15

Article (Published version)

Article (Accepted version)

Identifiers

PID : unige:47405
DOI : 10.1109/T-AFFC.2011.15

Additional URL for this publication

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5871728

Journal ISSN

1949-3045

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14047downloads

Creation

03/03/2015 16:36:03

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03/03/2015 16:36:03

Update

14/03/2023 22:56:37

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14/03/2023 22:56:36

Last indexation

30/10/2024 23:10:21

DEAP : a Database for Emotion Analysis Using Physiological Signals

Contributors

Published in

Publication date

Abstract

Keywords

UNIGE affiliation entities

UNIGE research groups

Citation (ISO format)

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