EmoPairCompete - Physiological Signals Dataset For Emotion and Frustration Assessment Under Team and Competitive Behaviours

Sneha Das, Nicklas Leander Lund, Carlos Ramos González, Nicole Nadine Lønfeldt

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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Abstract

We introduce a new dataset for emotion and stress (frustration) detection from physiological signals. Physiological signals are relevant in health applications like stress detection and monitoring or in mental health where emotion regulation often is of importance. The dataset contributes with the possibilities for disentangling a detailed emotional space (10 emotions) in relation to physiological signals, study dyads of prosocial behaviours vs teams of aggressive behaviours, and investigate continual learning or replication uncertainties.
Original languageEnglish
Title of host publicationProceedings of the ICLR 2024 Workshop on Learning from Time Series For Health (TS4H)
Number of pages10
Publication date2024
Publication statusPublished - 2024
EventICLR 2024 Workshop on Learning from Time Series For Health - Vienna, Austria
Duration: 11 May 202411 May 2024

Workshop

WorkshopICLR 2024 Workshop on Learning from Time Series For Health
Country/TerritoryAustria
CityVienna
Period11/05/202411/05/2024

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