A dataset of continuous affect annotations and physiological signals for emotion analysis
Sharma K, Van Den Broek EL, Albu-Schaeffer A, Schwenker F, Castellini C (2019)
Publication Type: Journal article
Publication year: 2019
Journal
Book Volume: 6
Article Number: 196
Journal Issue: 1
DOI: 10.1038/s41597-019-0209-0
Abstract
From a computational viewpoint, emotions continue to be intriguingly hard to understand. In research, a direct and real-time inspection in realistic settings is not possible. Discrete, indirect, post-hoc recordings are therefore the norm. As a result, proper emotion assessment remains a problematic issue. The Continuously Annotated Signals of Emotion (CASE) dataset provides a solution as it focusses on real-time continuous annotation of emotions, as experienced by the participants, while watching various videos. For this purpose, a novel, intuitive joystick-based annotation interface was developed, that allowed for simultaneous reporting of valence and arousal, that are instead often annotated independently. In parallel, eight high quality, synchronized physiological recordings (1000 Hz, 16-bit ADC) were obtained from ECG, BVP, EMG (3x), GSR (or EDA), respiration and skin temperature sensors. The dataset consists of the physiological and annotation data from 30 participants, 15 male and 15 female, who watched several validated video-stimuli. The validity of the emotion induction, as exemplified by the annotation and physiological data, is also presented.
Authors with CRIS profile
Involved external institutions
Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR) / German Aerospace Center
Germany (DE)
Universiteit Utrecht (UU) / Utrecht University
Netherlands (NL)
Universität Ulm
Germany (DE)
Germany (DE)
Universiteit Utrecht (UU) / Utrecht University
Netherlands (NL)
Universität Ulm
Germany (DE)
How to cite
APA:
Sharma, K., Van Den Broek, E.L., Albu-Schaeffer, A., Schwenker, F., & Castellini, C. (2019). A dataset of continuous affect annotations and physiological signals for emotion analysis. Scientific Data, 6(1). https://dx.doi.org/10.1038/s41597-019-0209-0
MLA:
Sharma, Karan, et al. "A dataset of continuous affect annotations and physiological signals for emotion analysis." Scientific Data 6.1 (2019).
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