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Perspective | Open Access

Soft Science

Kim et al. Soft Sci. 2026, 6, 26 DOI:10.20517/ss.2026.14

Wearable multimodal sensing for geriatric healthcare

Byungjin Kim, Shichao Ding , Joseph Wang *
*

Keywords:
Geriatric healthcare,
wearable hybrid sensors,
aging in place, predictive
digital health, multimodal
platforms, artificial
intelligence
Citation: Kim, B.; Ding, S.;
Wang, J. Wearable
multimodal sensing for
geriatric healthcare. Soft Sci.
2026, 6, 26.
https://dx.doi.org/10.20517
/ss.2026.14

Received: 26 Jan 2026
First Decision: 6 Feb
2026 Abstract
Revised: 20 Feb 2026
Accepted: 9 Mar 2026 Aging populations face growing multimorbidity, while episodic clinical assessments fail to
Published: 3 Apr 2026 capture gradual physiological changes unfolding during daily life. Although wearable
technologies enable continuous monitoring, single-modality systems provide incomplete
Academic Editor: and context-limited insight. This Perspective focuses on hybrid wearable sensors that
YongAn Huang
Copy Editor: integrate physical and chemical sensing for geriatric healthcare. Hybrid wearable sensing
Pei-Yun Wang provides a pathway toward continuous, predictive, and personalized geriatric health
Production Editor: management. By monitoring continuously multiple health parameters, such multimodal
Pei-Yun Wang
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.

INTRODUCTION
As life expectancy rises, multimorbidity increases, including diabetes, cardiovascular,

Aiiso Yufeng Li Family Department of Chemical and Nano Engineering, University of California San Diego, La Jolla, CA 92093, USA.

* Correspondence to: Dr. Shichao Ding, Prof. Joseph Wang, Aiiso Yufeng Li Family Department of Chemical and Nano Engineering,
University of California San Diego, La Jolla, CA 92093, USA. E-mail: dingshichao@westlake.edu.cn; josephwang@ucsd.edu

www.oaepublish.com Submit a Manuscript: https://ucenter.oaepublish.com