Wearable wisdom: How AI-powered devices are driving personalized preventive care

Garg, Venus (2025) Wearable wisdom: How AI-powered devices are driving personalized preventive care. World Journal of Advanced Engineering Technology and Sciences, 15 (3). pp. 196-206. ISSN 2582-8266

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Abstract

AI-powered wearable devices are transforming healthcare from reactive treatment to proactive wellness management through continuous physiological monitoring and personalized interventions. These advanced technologies incorporate sophisticated sensors that track multiple health parameters simultaneously, creating comprehensive digital health profiles while AI algorithms identify subtle patterns indicative of developing conditions. The real-time feedback mechanisms facilitate immediate lifestyle adjustments and behavioral changes, while personalized recommendations demonstrate significant effectiveness when properly contextualized and delivered at optimal moments. Clinical applications enable detection of subclinical conditions before symptom manifestation, potentially altering disease trajectories through early intervention. Beyond individual benefits, aggregated anonymous data offers unprecedented population health insights, enhancing epidemiological research and public health surveillance capabilities. Despite promising outcomes, challenges remain including sustained user engagement, healthcare system integration, regulatory frameworks, and ethical considerations around privacy and equity of access. The convergence of advanced sensing capabilities with Artificial Intelligence represents a fundamental shift in health monitoring that holds transformative potential for both individual and population-level health management.

Item Type: Article
Official URL: https://doi.org/10.30574/wjaets.2025.15.3.0908
Uncontrolled Keywords: Wearable Health Technology; Artificial Intelligence; Preventive Care; Personalized Health Monitoring; Early Intervention
Depositing User: Editor Engineering Section
Date Deposited: 16 Aug 2025 12:50
Related URLs:
URI: https://eprint.scholarsrepository.com/id/eprint/4395