可穿戴计算机
可穿戴技术
计算机科学
智能传感器
信号(编程语言)
活动识别
运动捕捉
嵌入式系统
光子学
极限(数学)
可扩展性
人机交互
远程病人监护
生物识别
医疗保健系统
人工智能
运动检测
人体运动
信号处理
实时计算
个性化医疗
结构健康监测
无线传感器网络
智能决策支持系统
系统工程
控制工程
深度学习
神经形态工程学
特征提取
智能手表
疾病监测
个性化
作者
Long Chen,Xinyu Li,Jian Lin Su,Qiang Xiao,Yu Ming Ning,Zhi Cai Yu,Ze Gu,Jie Xu,Zi Xuan Cai,Qing Chun Yin,Si Qi Huang,Qian Ma,W. LU,Jian Wei You,Tie Jun Cui
标识
DOI:10.1002/adma.202514150
摘要
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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