Liu, Z, Li, Z orcid.org/0000-0003-2583-5082, Zhai, H et al. (14 more authors) (2021) A highly sensitive stretchable strain sensor based on multi-functionalized fabric for respiration monitoring and identification. Chemical Engineering Journal, 426. 130869. ISSN 1385-8947
Abstract
Wearable strain sensors have generated considerable recent research interest due to their huge potential in the real-time detection of human body deformation. State-of-the-art strain sensors are normally fabricated through conductive networks with a single sensing element, which always faces the challenge of either limited stretchability or inferior quality in sensitivity. In this work, we report a highly sensitive strain sensor based on a multi-functionalized fabric through carbonization and polymer-assisted copper deposition. The sensor shows high sensitivity (Gauge factor ∼ 3557.6 in the strain range from 0 to 48%), and outstanding stretchability up to the strain of 300%, which is capable of detecting different types of deformation of the human body. By integrating the high-performance sensor with a deep learning network, we demonstrate a high-accuracy respiration monitoring and emergency alarm system, showing the enormous application potential of the sensor in personal and public healthcare.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 Elsevier B.V. All rights reserved. This is an author produced version of an article, published in Chemical Engineering Journal. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Strain sensor; Fiber functionalization; Wearable electronics; Copper deposition; Sensitivity enhancement |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 03 Feb 2022 14:37 |
Last Modified: | 17 Jun 2022 23:44 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.cej.2021.130869 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:183195 |