Researchers from the National University of Singapore and A*STAR’s Institute of Materials Research and Engineering have developed an AI-powered sensor patch called PETAL (Paper-like Battery-free In situ AI-enabled Multiplexed) for monitoring wound recovery.

The patch consists of five colorimetric sensors that detect and measure wound biomarkers such as temperature, pH, trimethylamine, uric acid, and moisture. The patch can be analyzed using a proprietary AI algorithm by recording an image or video on a mobile phone without removing it from the wound.

PETAL achieved 97% accuracy in distinguishing healing and non-healing chronic and burn wounds.

This technology is significant as it enables prompt and low-cost wound care management, potentially reducing complications and healthcare costs. Unlike existing wearable wound sensors, PETAL is thin, flexible, and biocompatible, allowing easy integration with wound dressing. The sensor can also be customized for other wound types by incorporating additional colorimetric sensors. The research team has filed an international patent and plans to conduct human clinical trials.

Article written by  Adam Ang



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