Flexible and Robust Metasurface‐Based Wearable Sensor for Intelligent Human Monitoring

Wearable sensors enabling noninvasive healthcare monitoring encounter significant challenges in preserving signal integrity under motion artifacts and mechanical deformation. Here, we present for the first time a wearable sensor that integrates topologically protected flexible metasurface technology, combining topological photonics with AI-enhanced sensing technology to enable multifunctional human monitoring. This intelligent system harnesses electromagnetic wave-body interactions to precisely capture cardiopulmonary dynamics, effectively overcoming the limitations of conventional wearable sensors in dynamic conditions. Specifically, the topological design of the sensor ensures stable operational performance even in bent or fractured states, while deep learning algorithms facilitate robust extraction of personalized biometric features to simultaneously achieve multiple healthcare functions, including vital sign monitoring, activity recognition, and individual identification. Experimental results demonstrate the system's capability for real-time health assessment across diverse scenarios, from exercise to rest states. By combining adaptive wearability with intelligent signal processing, this platform represents a transformative approach to next-generation smart healthcare systems, advancing applications from chronic disease management to AI-driven personalized healthcare.

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Publication Details

Journal
Advanced Materials
Published
2025-12-26
DOI
https://doi.org/10.1002/adma.202514150
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
0.00

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article

Flexible and Robust Metasurface‐Based Wearable Sensor for Intelligent Human Monitoring

Qiang Xiao, Ze Gu, Zhi Cai Yu, Xinyu Li et al.
Advanced Materials
Advanced Sensor and Energy Harvesting Materials
article

Flexible and Robust Metasurface‐Based Wearable Sensor for Intelligent Human Monitoring

Qiang Xiao, Ze Gu, Zhi Cai Yu, Xinyu Li, W. LU, Tie Jun Cui, Jian Wei You, Qing Chun Yin, Si Qi Huang, Yu Ming Ning, Zi Xuan Cai, Jian Lin Su, Jie Xu, Long Chen, Qian Ma
article en

Abstract

Wearable sensors enabling noninvasive healthcare monitoring encounter significant challenges in preserving signal integrity under motion artifacts and mechanical deformation. Here, we present for the first time a wearable sensor that integrates topologically protected flexible metasurface technology, combining topological photonics with AI-enhanced sensing technology to enable multifunctional human monitoring. This intelligent system harnesses electromagnetic wave-body interactions to precisely capture cardiopulmonary dynamics, effectively overcoming the limitations of conventional wearable sensors in dynamic conditions. Specifically, the topological design of the sensor ensures stable operational performance even in bent or fractured states, while deep learning algorithms facilitate robust extraction of personalized biometric features to simultaneously achieve multiple healthcare functions, including vital sign monitoring, activity recognition, and individual identification. Experimental results demonstrate the system's capability for real-time health assessment across diverse scenarios, from exercise to rest states. By combining adaptive wearability with intelligent signal processing, this platform represents a transformative approach to next-generation smart healthcare systems, advancing applications from chronic disease management to AI-driven personalized healthcare.

Advanced MaterialsVol. 38(10)
Donghua University (CN), Southeast University (BD), Suzhou Research Institute (CN), Southeast University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Government of Jiangsu Province, Natural Science Foundation of Jiangsu Province, Higher Education Discipline Innovation Project, Jiangsu Planned Projects for Postdoctoral Research Funds, National Key Research and Development Program of China
Openalex Percentile: Top 42%
Advanced Sensor and Energy Harvesting Materials
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