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

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Battery-free and AI-enabled multiplexed sensor patches for wound monitoring
Title:
Battery-free and AI-enabled multiplexed sensor patches for wound monitoring
Journal Title:
Science Advances
Publication Date:
16 June 2023
Citation:
Zheng, X. T., Yang, Z., Sutarlie, L., Thangaveloo, M., Yu, Y., Salleh, N. A. B. M., Chin, J. S., Xiong, Z., Becker, D. L., Loh, X. J., Tee, B. C. K., & Su, X. (2023). Battery-free and AI-enabled multiplexed sensor patches for wound monitoring. Science Advances, 9(24). https://doi.org/10.1126/sciadv.adg6670
Abstract:
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.
License type:
Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
Funding Info:
This research / project is supported by the A*STAR - Additive Manufacturing of Biological Materials (AMBM) program
Grant Reference no. : A18A8b0059

This research / project is supported by the A*STAR - IAF-PP grant
Grant Reference no. : H1701a0004

This research / project is supported by the National Research Foundation (NRF), Prime Minister's office - NRF Fellowship
Grant Reference no. : NRFF-2017-08

This research / project is supported by the A*STAR - Industry Alignment Fund-Pre-Positioning Programme (IAF-PP), Wound Care Innovation for the Tropics (WCIT) Programme
Grant Reference no. : H17/01/a0/0C9

This research / project is supported by the A*STAR, The Skin Research Institute of Singapore - Phase 2: SRIS@Novena
Grant Reference no. : NA

This research / project is supported by the National University of Singapore (NUS) - iHealthtech grant
Grant Reference no. : NA
Description:
ISSN:
2375-2548