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

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 multi-plexed (PETAL) sensor for holistic wound assessment by leveraging deep learning algorithms. This sensor con-sists 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 pro-gression or severity is demonstrated. This PETAL sensor allows early warning of adverse events, which could trigger immediate clinical intervention to facilitate wound care management.

Automated summary

This study presents a battery-free paper-based sensor that utilizes deep learning algorithms to comprehensively assess wounds, including inflammation and infection. The sensor consists of a wax-printed paper panel with five colorimetric sensors for measuring temperature, pH, trimethylamine, uric acid, and moisture. By analyzing sensor images captured by a mobile phone using neural network-based machine learning algorithms, the healing status of wounds can be determined. The sensor can accurately classify healing versus non-healing status with up to 97% accuracy in ex situ experiments using exudates collected from rat perturbed wounds and burn wounds. In situ monitoring of wound progression and severity is demonstrated by attaching the sensor patches to rat burn wound models. This PETAL sensor enables early warning of adverse events, facilitating prompt clinical intervention for wound care management.