Multimodal Emotion Recognition and Affective Computing
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Neuroscience and Neural Engineering".
Deadline for manuscript submissions: 20 April 2026 | Viewed by 374
Special Issue Editors
Interests: digital sound processing and analyis; EEG/MEG brain signal analysis
Special Issues, Collections and Topics in MDPI journals
Interests: digital signal processing; musical acoustics; EEG-NIRS processing and new educational methods
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue aims to bring together contributions on machine learning and deep learning methods for recognizing human emotions and cognitive states from a variety of modalities, including brain signals (EEG, fNIRS), physiological signals (ECG, EDA, respiration), speech, facial expressions, body motion and multimodal data fusion. Applications in human–computer interaction, healthcare, education, entertainment and VR/AR environments would also be emphasized.
Given the increasing interest in emotion-aware and human-centered AI systems, I believe this theme would appeal to a wide community of researchers and practitioners.
Dr. Athanasios Koutras
Dr. Ana Maria Barbancho
Guest Editors
Manuscript Submission Information
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Keywords
- emotion recognition
- affective computing
- multimodal fusion
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