Flexible and Robust Metasurface‐Based Wearable Sensor for Intelligent Human Monitoring
Abstract
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.
Article Details
Authors (15)
Long Chen
Department of Chemistry, Frontiers Science Center for New Organic Matter and State Key Laboratory of Advanced Chemical Power Sources, College of Chemistry
Xin Yu Li
State Key Laboratory of Millimeter Wave Southeast University Nanjing China
Jian Lin Su
Qiang Xiao
Yu Ming Ning
Zhi Cai Yu
State Key Laboratory of Millimeter Wave School of Information Science and Engineering Southeast University Nanjing China
Ze Gu
Jie Xu
Zi Xuan Cai
State Key Laboratory of Millimeter Wave Southeast University Nanjing China
Qing Chun Yin
State Key Laboratory of Millimeter Wave School of Information Science and Engineering Southeast University Nanjing China
Si Qi Huang
State Key Laboratory of Millimeter Wave School of Information Science and Engineering Southeast University Nanjing China
Qian Ma
State Key Laboratory of Electroanalytical Chemistry
Wei Bing Lu
State Key Laboratory of Millimeter Wave School of Information Science and Engineering Southeast University Nanjing China
Jian Wei You
Tie Jun Cui