材料科学
可穿戴计算机
接口(物质)
检出限
压力(语言学)
压力传感器
信号(编程语言)
可穿戴技术
胶粘剂
声学
极限(数学)
噪音(视频)
模数
灵敏度(控制系统)
光电子学
纳米技术
复合材料
计算机科学
电子工程
嵌入式系统
机械工程
人工智能
毛细管作用
程序设计语言
图层(电子)
数学分析
哲学
工程类
物理
毛细管数
图像(数学)
数学
统计
语言学
作者
Lingjie Xie,Lei Hao,Yina Liu,Bohan Lu,Xuan Qin,Cheng‐Yi Zhu,Haifeng Ji,Zhenqiu Gao,Yifan Wang,Yang‐Yang Lv,Chun Zhao,Ivona Z. Mitrović,Xuhui Sun,Zhen Wen
标识
DOI:10.1002/adma.202406235
摘要
Abstract The great challenges for existing wearable pressure sensors are the degradation of sensing performance and weak interfacial adhesion owing to the low mechanical transfer efficiency and interfacial differences at the skin–sensor interface. Here, an ultrasensitive wearable pressure sensor is reported by introducing a stress‐concentrated tip‐array design and self‐adhesive interface for improving the detection limit. A bipyramidal microstructure with various Young's moduli is designed to improve mechanical transfer efficiency from 72.6% to 98.4%. By increasing the difference in modulus, it also mechanically amplifies the sensitivity to 8.5 V kPa −1 with a detection limit of 0.14 Pa. The self‐adhesive hydrogel is developed to strengthen the sensor–skin interface, which allows stable signals for long‐term and real‐time monitoring. It enables generating high signal‐to‐noise ratios and multifeatures when wirelessly monitoring weak pulse signals and eye muscle movements. Finally, combined with a deep learning bimodal fused network, the accuracy of fatigued driving identification is significantly increased to 95.6%.
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