A Flexible-Integrated Multimodal Hydrogel-Based Sensing Patch

被引:0
|
作者
Wang, Peng [2 ]
Wang, Guoqing [1 ]
Sun, Guifen [3 ]
Bao, Chenchen [1 ]
Li, Yang [1 ,4 ,6 ]
Meng, Chuizhou [3 ]
Yao, Zhao [5 ]
机构
[1] Univ Jinan, Sch Informat Sci & Engn, Jinan 250022, Peoples R China
[2] Univ Jinan, Sch Mech Engn, Jinan 250022, Peoples R China
[3] Hebei Univ Technol, Engn Res Ctr,Minist Educ Intelligent Rehabil Devic, Sch Mech Engn,Hebei Key Lab Smart Sensing & Human, State Key Lab Reliabil & Intelligence Elect Equipm, Tianjin 300401, Peoples R China
[4] Shandong Univ, Sch Integrated Circuits, Jinan 250101, Peoples R China
[5] Qingdao Univ, Coll Elect & Informat, Qingdao 266071, Peoples R China
[6] Fudan Univ, State Key Lab Integrated Chips & Syst, Shanghai 200433, Peoples R China
关键词
Multimodal sensing; Proximity sensor; Pressure sensor; Temperature sensor; Electrospun nanofibers; SENSOR;
D O I
10.1007/s40820-025-01656-w
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
Sleep monitoring is an important part of health management because sleep quality is crucial for restoration of human health. However, current commercial products of polysomnography are cumbersome with connecting wires and state-of-the-art flexible sensors are still interferential for being attached to the body. Herein, we develop a flexible-integrated multimodal sensing patch based on hydrogel and its application in unconstraint sleep monitoring. The patch comprises a bottom hydrogel-based dual-mode pressure-temperature sensing layer and a top electrospun nanofiber-based non-contact detection layer as one integrated device. The hydrogel as core substrate exhibits strong toughness and water retention, and the multimodal sensing of temperature, pressure, and non-contact proximity is realized based on different sensing mechanisms with no crosstalk interference. The multimodal sensing function is verified in a simulated real-world scenario by a robotic hand grasping objects to validate its practicability. Multiple multimodal sensing patches integrated on different locations of a pillow are assembled for intelligent sleep monitoring. Versatile human-pillow interaction information as well as their evolution over time are acquired and analyzed by a one-dimensional convolutional neural network. Track of head movement and recognition of bad patterns that may lead to poor sleep are achieved, which provides a promising approach for sleep monitoring.
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页数:19
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