Advancing emotion recognition with Virtual Reality: A multimodal approach using physiological signals and machine learning.

Journal: Computers in biology and medicine

Published Date: Jul 1, 2025

Abstract

INTRODUCTION: Emotion recognition systems have traditionally relied on basic visual elicitation. Virtual reality (VR) offers an immersive alternative that better resembles real-world emotional experiences.

Authors

Edoardo Maria Polo

SpinLabs, Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy.
Francesco Iacomi

Politecnico di Milano, Piazza Leonardo da Vinci, 32, Milan, 20133, Italy.
Alberto Valdes Rey

Politecnico di Milano, Piazza Leonardo da Vinci, 32, Milan, 20133, Italy.
Davide Ferraris

Lega Italiana Per La Lotta Contro I Tumori - LILT, Via Giacomo Venezian, 1, Milan, 20133, Italy.
Alessia Paglialonga

Institute of Electronics, Computer and Telecommunication Engineering (IEIIT), National Research Council of Italy (CNR), Milan, Italy.
Riccardo Barbieri

SpinLabs, Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy.

Keywords

Adult Electrocardiography Emotions Female Galvanic Skin Response Humans Machine Learning Male Signal Processing, Computer-Assisted Virtual Reality Young Adult

External Resources

View on PubMed Access via DOI PubMed (40424763)

Advancing emotion recognition with Virtual Reality: A multimodal approach using physiological signals and machine learning.

Abstract

Authors

Keywords

External Resources

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