AI-Driven Ambient Intelligence Systems for Mental Health Monitoring and Proactive Intervention
DOI:
https://doi.org/10.48047/exn63q47Keywords:
Mental Health Monitoring, Proactive Intervention, Multimodal Sensing, Explainable AI, Personalized Interventions, Ethical AI.Abstract
The swift increasing number of mental health challenges worldwide demands prompt development of contemporary and extensive
proactive solutions for managing mental health. This paper researches how AmI combines with AI capabilities to alter mental health
tracking as well as intervention approaches. The paper provides an in-depth examination that explains the basic concepts of AmI
together with its applications for mental health surveillance and proactive intervention delivery. The study analyzes the processing
of mental health diagnostic information from physiological and behavioral elements with contextual factors yet examines the need
for explaining AI models while ensuring ethical use and fairness of AI diagnostics.
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References
Acampora, G., Cook, D. J., Rashidi, P., & Vasilakos, A. V. (2013). A Survey on Ambient Intelligence in Healthcare. Proceedings of the IEEE, 101(12), 2470–2494. https://doi.org/10.1109/jproc.2013.2262913 [2] Gams, M., Gu, I. Y. H., Härmä, A., Muñoz, A., & Tam, V. (2019). Artificial intelligence and ambient intelligence. Journal of Ambient Intelligence and Smart Environments, 11(1), 71-86. [3] Hansmann, U., Merk, L., Nicklous, M. S., & Stober, T. (2013). Pervasive computing handbook. Springer Science & Business Media.
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