We've never been eye to eye: a pupillometry pipeline for the detection of stress and negative affect in remote working scenarios

  • In this paper, we present a processing pipeline for the analysis of stress and negative affect based on pupillometry. We were able to show that it is possible to extract meaningful pupil features from video data recorded by an infrared- (IR-) sensitive webcam and successfully trained a Support Vector Machine on the corresponding dataset. Further, we conducted a study that shows that the proposed pipeline is suitable for the assessment of stress as well as negative affect during stress eliciting situations in a digital environment.

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Metadaten
Author:Alexander HeimerlGND, Linda Becker, Dominik SchillerGND, Tobias BaurORCiDGND, Fabian Wildgrube, Nicolas Rohleder, Elisabeth AndréORCiDGND
URN:urn:nbn:de:bvb:384-opus4-1015731
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/101573
ISBN:978-1-4503-9631-8OPAC
Parent Title (English):PETRA '22: proceedings of the 15th International Conference on Pervasive Technologies Related to Assistive Environments, 29 June - 1 July 2022, Corfu, Greece
Publisher:ACM
Place of publication:New York, NY
Editor:Fillia Makedon
Type:Conference Proceeding
Language:English
Year of first Publication:2022
Publishing Institution:Universität Augsburg
Release Date:2023/02/06
First Page:486
Last Page:493
DOI:https://doi.org/10.1145/3529190.3534729
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Menschzentrierte Künstliche Intelligenz
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):Sonstige Open-Access-Lizenz

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