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Affective computing in anxiety disorders: A rapid literature review of emotion recognition applications

Moretti, Luigi; Thompson, Miles; Matthews, Paul; Loizou, Michael; Western, David

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Authors

Luigi Moretti

Paul Matthews

Profile image of Michael Loizou

Dr Michael Loizou Michael2.Loizou@uwe.ac.uk
Wallscourt Associate Professor in Health Technology and Life Sciences

Profile image of David Western

David Western David.Western@uwe.ac.uk
Wallscourt Fellow in Health Technology



Abstract

Anxiety disorders (ADs) affect roughly one in ten people in the UK, and this number is expected to increase, intensifying the need for innovation. Digital technologies such as affective computing (AC, technology to detect human emotions) could foster a more patient-centric approach, enhancing therapy adherence and optimizing clinician-patient interactions. This paper reviews the literature relevant to the integration of affective computing in clinical pathways for ADs. A search was conducted on Google Scholar and PubMed using the keywords “affective computing” and subtypes of anxiety disorders. A total of 355 results were filtered to focus on peer-reviewed articles that specifically addressed emotion recognition in pathological anxiety as opposed to simply feeling anxious. Findings underscore prevalent studies focusing on post-traumatic stress disorder (PTSD) and the widespread use of valence and arousal for emotion quantification. Various approaches for both eliciting and detecting emotions are explored, offering technical and practical insights. Diverse applications, from monitoring treatment progression in behavioral therapies to assessing the efficiency of deep brain stimulation for intractable obsessive-compulsive disorder, highlight affective computing's versatility and promise. A significant advantage of digital technologies is their potential to capture longitudinal and contextualized data beyond clinical confines. Such assessments elucidate patients' daily challenges and triggers, enabling tailored interventions. The literature suggests that AC has the potential to support mental healthcare and improve patient outcomes. However, further evidence of its effective benefits is required, especially for ADs beyond PTSD, and further exploration of its implementation in clinical pathways is needed.

Presentation Conference Type Conference Paper (published)
Conference Name 18th International Joint Conference on Biomedical Engineering Systems and Technologies
Start Date Feb 20, 2025
End Date Feb 22, 2025
Acceptance Date Jan 31, 2025
Publication Date Mar 14, 2025
Deposit Date Jun 13, 2025
Publicly Available Date Jun 13, 2025
Peer Reviewed Peer Reviewed
Pages 273-284
Book Title Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies
ISBN 9789897587313
DOI https://doi.org/10.5220/0013322800003911
Public URL https://uwe-repository.worktribe.com/output/13946279