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

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

Science Advances

10.1126/sciadv.adg6670

http://dx.doi.org/10.1126/sciadv.adg6670

Xin Ting Zheng, Zijie Yang, Laura Sutarlie, Moogaambikai Thangaveloo, Yong Yu, Nur Asinah Binte Mohamed Salleh, Jiah Shin Chin, Ze Xiong, David Lawrence Becker, Xian Jun Loh, Benjamin C. K. Tee, Xiaodi Su

Multidisciplinary

16 June 2023

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

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.

Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)

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

https://oar.a-star.edu.sg/communities-collections/articles/19644

2375-2548

Institute of Materials Research and Engineering

https://doi.org/10.1126/sciadv.adg6670