Wearable multimodal sensing for geriatric healthcare

Abstract

Aging populations face growing multimorbidity, while episodic clinical assessments fail to capture gradual physiological changes unfolding during daily life. Although wearable technologies enable continuous monitoring, single-modality systems provide incomplete and context-limited insight. This Perspective focuses on hybrid wearable sensors that integrate physical and chemical sensing for geriatric healthcare. Hybrid wearable sensing provides a pathway toward continuous, predictive, and personalized geriatric health management. By monitoring continuously multiple health parameters, such multimodal systems have distinct advantages for real-time monitoring, including early risk detection and more personalized health assessment through the integration of complementary physical and biochemical signals. We discuss recent advances in wearable physical sensors, alongside with emerging wearable chemical sensors, then argue that chem-phys hybrid integration enables more interpretable and clinically actionable assessment of aging trajectories than single-modality wearable systems. Finally, we discuss translational requirements and future prospects, including robust real-world operation, AI-driven inference, and integration with telemedicine and home-based care.

Keywords

Geriatric healthcare / wearable hybrid sensors / aging in place / predictive digital health / multimodal platforms / artificial intelligence

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