Autonomous Robot-Driven Chronic Wound 3D Reconstruction and Analysis System

Chronic wounds require accurate and objective assessment to monitor healing progress and optimize treatment. Traditional contact-based methods for wound measurement are often uncomfortable for patients, impractical for clinicians, and prone to inaccuracies due to the complex shapes of wounds. Advances in computational power and data analysis have enabled non-contact techniques, particularly digital imaging, to play a greater role in wound assessment. However, challenges persist, as chronic wounds can vary greatly in size, shape, and surface geometry, making accurate 3D modeling difficult. Dynamic changes in wound dimensions during treatment and the potential for occluded areas further complicate assessment. Handheld 3D cameras and sensors, while promising, are limited by user experience and the potential for incomplete reconstructions. To address these challenges, this paper introduces a fully automated system for analyzing chronic wounds. The system consists of a robotic arm, an industrial-grade 3D scanner, and advanced algorithms for extracting and analyzing wound features. This complete pipeline improves the robustness and functionality of the system and enables precise 3D wound modeling and comprehensive data extraction. This paper discusses the operational system, highlights its advancements, and evaluates its potential for enhancing wound monitoring and healing outcomes.