Battery-free and AI-enabled multiplexed sensor patches for wound monitoring

doi:10.1126/sciadv.adg6670

	Battery-free and AI-enabled multiplexed sensor patches for wound monitoring
	Zheng, Xin Ting 1; Yang, Zijie 2,3; Sutarlie, Laura 1; Thangaveloo, Moogaambikai 4,5; Yu, Yong 1; Salleh, Nur Asinah Binte 1; Chin, Jiah Shin 4,6; Xiong, Ze3,7,8 ; Becker, David Lawrence 4,5; Loh, Xian Jun 1; Tee, Benjamin C.K.2,3,9,10; Su, Xiaodi 1,11
	2023-06
发表期刊	SCIENCE ADVANCES (IF:11.7[JCR-2023],13.7[5-Year])
ISSN	2375-2548
EISSN	2375-2548
卷号	9 期号:24
发表状态	已发表
DOI	10.1126/sciadv.adg6670
摘要	Wound healing is a dynamic process with multiple phases. Rapid profiling and quantitative characterization of inflammation and infection remain challenging. We report a paper-like battery-free in situ AI-enabled multiplexed (PETAL) sensor for holistic wound assessment by leveraging deep learning algorithms. This sensor consists of a wax-printed paper panel with five colorimetric sensors for temperature, pH, trimethylamine, uric acid, and moisture. Sensor images captured by a mobile phone were analyzed by neural network-based machine learning algorithms to determine healing status. For ex situ detection via exudates collected from rat perturbed wounds and burn wounds, the PETAL sensor can classify healing versus nonhealing status with an accuracy as high as 97%. With the sensor patches attached on rat burn wound models, in situ monitoring of wound progression or severity is demonstrated. This PETAL sensor allows early warning of adverse events, which could trigger immediate clinical intervention to facilitate wound care management. © 2023 The Authors.
关键词	Deep learning Electric batteries Learning algorithms Battery-free Colorimetric sensors Dynamic process Multiplexed sensors Paper-like Printed papers Quantitative characterization Trimethyl amine Wound assessment Wound healing
收录类别	EI
语种	英语
出版者	American Association for the Advancement of Science
EI入藏号	20233614672651
EI主题词	Rats
EI分类号	461.4 Ergonomics and Human Factors Engineering ; 702.1 Electric Batteries ; 723.4.2 Machine Learning
原始文献类型	Journal article (JA)
引用统计	被引频次：59[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/329003
专题	生物医学工程学院生物医学工程学院_PI研究组_熊泽组
通讯作者	Tee, Benjamin C.K.; Su, Xiaodi
作者单位	1.Institute of Materials Research and Engineering (IMRE), Agency for Science Technology and Research (ASTAR), 2 Fusionopolis Way, Innovis #08-03, Singapore; 138634, Singapore; 2.Department of Materials Science and Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore; 117576, Singapore; 3.Institute for Health Innovation and Technology (iHealthtech), National University of Singapore, MD6, 14 Medical Drive, Singapore; 117599, Singapore; 4.Lee Kong Chian School of Medicine, Nanyang Technological University, 11 Mandalay Road, Singapore; 308232, Singapore; 5.Skin Research Institute of Singapore (SRIS), Agency for Science Technology and Research (ASTAR), 11 Mandalay Road, Singapore; 308232, Singapore; 6.AStar Skin Research Laboratory (ASRL), Agency for Science Technology and Research (ASTAR), 11 Mandalay Road, Singapore; 308232, Singapore; 7.Department of Biomedical Engineering, National University of Singapore, Singapore; 117576, Singapore; 8.Wireless and Smart Bioelectronics Lab, School of Biomedical Engineering, ShanghaiTech University, Shanghai; 201210, China; 9.The N.1 Institute for Health, National University of Singapore, 28 Medical Drive #05-COR, Singapore; 117456, Singapore; 10.Department of Electrical and Computer Engineering, National University of Singapore, Block E4, 4 Engineering Drive 3, Singapore; 117583, Singapore; 11.Department of Chemistry, National University of Singapore, Block S8, level 3, 3 Science Drive 3, Singapore; 117543, Singapore
推荐引用方式 GB/T 7714	Zheng, Xin Ting,Yang, Zijie,Sutarlie, Laura,et al. Battery-free and AI-enabled multiplexed sensor patches for wound monitoring[J]. SCIENCE ADVANCES,2023,9(24).
APA	Zheng, Xin Ting.,Yang, Zijie.,Sutarlie, Laura.,Thangaveloo, Moogaambikai.,Yu, Yong.,...&Su, Xiaodi.(2023).Battery-free and AI-enabled multiplexed sensor patches for wound monitoring.SCIENCE ADVANCES,9(24).
MLA	Zheng, Xin Ting,et al."Battery-free and AI-enabled multiplexed sensor patches for wound monitoring".SCIENCE ADVANCES 9.24(2023).