Emotion recognition systems with electrodermal activity : From affective science to affective computing
D'Amelio, Tomás Ariel (Centre de Recerca Matemàtica)
Galán, Lorenzo A. (Universidad de Buenos Aires. Instituto de Investigaciones)
Maldonado, Emmanuel Alesandro (Universidad Favaloro)
Díaz Barquinero, Agustín Ariel (Universidad Favaloro)
Rodríguez Cuello, Jerónimo (Universidad Favaloro)
Bruno, Nicolás Marcelo (Institut du Cerveau et de la Moëlle épinière (París, França))
Tagliazucchi, Enzo (Universidad de San Andrés. Centro de Neurociencia Cognitiva)
Engemann, Denis Alexander (Roche Innovation Center Basel. Neuroscience and Rare Diseases)

Data:	2025
Resum:	Affective computing is an interdisciplinary field that aims to automatically recognize and interpret emotions. Recent research has focused on using physiological signals (e. g. , electrodermal activity) to improve emotion recognition. However, the theoretical emotion models that underlie these systems have received comparatively little attention. We conducted a systematic review and meta-analysis on electrodermal-activity-based emotion-recognition systems. Our findings suggest that arousal prediction models outperform valence prediction models, supporting our preregistered hypothesis. This correlates with arousal's association with autonomic nervous system activity and its direct link to electrodermal activity. We also observed a mismatch between the machine-learning approaches most often used-chiefly classification models-and the predominantly dimensional emotion frameworks adopted in the literature. Specifically, although dimensional affective models are increasingly popular, there has not been a parallel rise in regression models that would better reflect the continuous nature of the underlying data. We conclude that a comprehensive understanding of affective states requires consideration of both psychological and computational perspectives in affective computing research.
Ajuts:	European Commission 101126533
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Affective computing ; Emotion recognition ; Electrodermal activity ; Emotion models ; Systematic review ; Meta-analysis
Publicat a:	Neurocomputing, Vol. 651 (October 2025) , art. 130831, ISSN 1872-8286

DOI: 10.1016/j.neucom.2025.130831

23 p, 8.2 MB

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