A real-world dataset of group emotion experiences based on physiological data

Patrícia Bota*, Joana Brito, Ana Fred, Pablo Cesar, Hugo Silva

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Affective computing has experienced substantial advancements in recognizing emotions through image and facial expression analysis. However, the incorporation of physiological data remains constrained. Emotion recognition with physiological data shows promising results in controlled experiments but lacks generalization to real-world settings. To address this, we present G-REx, a dataset for real-world affective computing. We collected physiological data (photoplethysmography and electrodermal activity) using a wrist-worn device during long-duration movie sessions. Emotion annotations were retrospectively performed on segments with elevated physiological responses. The dataset includes over 31 movie sessions, totaling 380 h+ of data from 190+ subjects. The data were collected in a group setting, which can give further context to emotion recognition systems. Our setup aims to be easily replicable in any real-life scenario, facilitating the collection of large datasets for novel affective computing systems.

Original languageEnglish
Article number116
Number of pages17
JournalScientific Data
Volume11
Issue number1
DOIs
Publication statusPublished - 2024

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