Design and Validation of a Wearable Imaging System for Automated Wound Monitoring in Porcine Model
Wan Shen HeeiD, Maryam TebyaniiD, Prabhat BaniyaiD, Celeste Franco, Gordon KelleriD, Fan LuiD, Houpu LiiD, Narges AsefifeyzabadiiD, Hsin‐ya YangiD, Guillermo Villa-MartineziD, Kaelan Schorger, Koushik Devarajan, Alexie BarbeeiD, Cristian Hernandez, Tiffany NguyeniD, Marcella M. GomeziD, R. Rivkah IsseroffiD, Marco RolandiiD, Mircea TeodorescuiD
Abstract
Effective wound monitoring has the potential to guide treatment regiments and improve healing outcomes, yet current clinical assessment methods remain largely subjective and labor-intensive. To address this challenge, we present a high-resolution wearable imaging system designed for continuous wound monitoring. The system integrates a 64 MP camera with a plano-convex lens housed in an enclosure measuring 73 mm in diameter and 36.1 mm in height, and features a custom printed circuit board (PCB) for programmable LED illumination. The 3D-printed device enclosure is designed to accommodate a silicone bioelectronic device and can be securely attached using a commercially available ostomy skin barrier. In porcine model validation studies, the system successfully captured daily wound progression over periods up to 7 days. The captured images were wirelessly transmitted to a processing unit where DeepMapper, a machine learning algorithm, processed z-stacked images and performed multi-level feature extraction to predict wound healing stages and indicate potential complications such as infection. This imaging system enables automated analysis of wound progression and supports the development of smart wound care platforms for personalized treatment strategies. The integrated design approach demonstrates the feasibility of creating compact, high-resolution imaging systems suitable for clinical wound monitoring applications.
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