PERSPECTIVE article
Front. Comput. Sci.
Sec. Human-Media Interaction
This article is part of the Research TopicHuman Behavior in Extreme Conditions: Novel Approaches and TechnologiesView all 10 articles
AI Affective Computing and Behavioral Health
Provisionally accepted
Vanessa Farsadaki1,2,3,4*
Charla Griffy-Brown1- 1Thunderbird School of Global Management, Arizona State University, Tempe, United States
- 2Space Exploration Strategies, Houston, United States
- 3Kepler Space University, Bradenton, United States
- 4The British Interplanetary Society, London, United Kingdom
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The integration of artificial intelligence (AI) and affective computing into behavioral health is transforming how mental well-being is assessed, monitored, and treated. As emotional and cognitive states can now be inferred through facial expressions, vocal tone, physiological signals, and behavioral cues, new technological paradigms are emerging to complement traditional approaches to mental healthcare. This is especially relevant in the wake of rising global mental health challenges, where access, personalization, and real-time feedback are essential components of effective care. Affective computing, a multidisciplinary field at the intersection of psychology, computer science, and cognitive science, seeks to enable machines to recognize, interpret, and respond to human emotions. When coupled with AI-driven data analytics and virtual reality (VR), it offers powerful tools for enhancing self-awareness, supporting clinical diagnostics, and delivering immersive therapeutic interventions. This paper explores how AI and affective computing can be leveraged across the behavioral health spectrum, from early detection and remote monitoring to therapy delivery and outcome prediction, with a particular emphasis on virtual environments as mediators of emotionally adaptive systems. We aim to review current innovations, examine their psychological validity, discuss ethical implications, and propose a research framework for advancing human-centered AI in behavioral health. Through this lens, we highlight the potential of emotionally intelligent systems not only to augment clinical practice but also to empower users in managing their mental well-being in real time.
Keywords: Affective Computing, behavioral health, artificial intelligence, Virtual reality (VR), Digital phenotyping
Received: 06 Sep 2025; Accepted: 25 Nov 2025.
Copyright: © 2025 Farsadaki and Griffy-Brown. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Vanessa Farsadaki
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