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Dataset . 2023
Data sources: Datacite
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Dataset . 2023
Data sources: ZENODO
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Dataset . 2023
Data sources: ZENODO
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Dataset . 2025
Data sources: ZENODO
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Dataset . 2025
Data sources: Datacite
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Dataset . 2023
Data sources: Datacite
ZENODO
Dataset . 2025
Data sources: Datacite
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Claim

EmpathicSchool: A multimodal dataset for real-time facial expressions and physiological data analysis under different stress conditions

Research datakeyboard_double_arrow_right Dataset 12 Feb 2023 English Publisher:Zenodo
Authors: Hosseini, Majid; Sohrab, Fahad; Raju Gottumukkala; Ravi Teja Bhupatiraju; Satya Katragadda; Raitoharju, Jenni; Iosifidis, Alexandros; +1 Authors

doi: 10.5281/zenodo.7097178 , 10.5281/zenodo.7097177 , 10.5281/zenodo.7372497 , 10.5281/zenodo.15556502

EmpathicSchool: A multimodal dataset for real-time facial expressions and physiological data analysis under different stress conditions

Abstract

EmpathicSchool is a novel dataset that captures facial expressions and the associated physiological signals, such as heart rate, electrodermal activity, and skin temperature, under different stress levels. The data was collected from 20 participants at different sessions for 26 hours. The data includes 7 different signal types, including both computer vision and physiological features that can be used to detect stress. In addition, various experiments were conducted to validate the signal quality.

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Keywords

stress detection, emotions, biometric feedbacks, computer vision, multimodal

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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1
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