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Gao et al., “AI-powered closed-loop wearable bioelectronics for personalized and autonomous healthcare”
A Nature Sensors review argues that AI-powered closed-loop wearables could move healthcare devices beyond passive data collection by connecting continuous biosensing directly to AI-guided decisions and therapeutic intervention. The authors emphasize that clinical value depends on the coordinated system—sensing, control, treatment, and human oversight—not any component alone. Long-term interface stability, robust control, transparent safety mechanisms, and evidence of patient benefit remain prerequisites for scalable use.
Closing the loop between sensing and treatment could personalize continuous care, but it also turns model reliability, oversight, and health-data protection into immediate safety requirements.
Why it matters
A device that autonomously changes therapy sits in a different risk category from a fitness tracker. Errors can become interventions, so safe deployment requires bounded control, clear override paths, continuous validation, and a defined role for clinicians and patients.
The article is a system-level review and roadmap, not evidence that a single mature platform is ready for broad clinical use. Its contribution is to define the engineering and governance conditions under which promising prototypes could become trustworthy care infrastructure.
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