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Home-based Detection and Prediction of Diabetic Foot Ulcers at Early Stage Using Sensor Technology and Supervised Learning

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Journal of Harbin Institute of Technology(New Series) 2024年第1期31卷 26-37页

作者： Kamasamudram Bhavya Sai Rishi Raghu Sai Surya Varshith Nukala Jayashree Jayaraman Vijayashree Jayaraman School of Computer Science and Engineering Vellore Institute of TechnologyVellore 632014India

For years,foot ulcers linked with diabetes mellitus and neuropathy have significantly impacted diabetic patients’ health-related quality of life(HRQoL). Diabetes foot ulcers impact15% of all diabetic patients at some point in their lives. The facilities and resources used for DFU detection and treatment are only available at hospitals and clinics,which results in the unavailability of feasible and timely detection at an early stage. This necessitates the development of an at-home DFU detection system that enables timely predictions and seamless communication with users,thereby preventing amputations due to neglect and severity. This paper proposes a feasible system consisting of three major modules:an IoT device that works to sense foot nodes to send vibrations onto a foot sole,a machine learning model based on supervised learning which predicts the level of severity of the DFU using four different classification techniques including XGBoost,K-SVM,Random Forest,and Decision tree,and a mobile application that acts as an interface between the sensors and the patient. Based on the severity levels,necessary steps for prevention,treatment,and medications are recommended via the application.

关键词： diabetic foot ulcer podiatry diabetes mellitus healthcare footcare internet of things machine learning human⁃computer interaction

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