I. A Frame Work of a Smart Therapeutic Insole System By Measuring Plantar Pressure For Early Diagnosis Of Diabetic Foot Ulcers Using Machine Learning And Thermal Imaging Techniques

Diabetic Foot Ulcers (DFUs) are a significant complication of diabetes, often resulting in severe morbidity, infections, and amputations. Early diagnosis of DFUs is critical in preventing these complications. This paper focuses on the frame work of a smart therapeutic insole system that integrates machine learning and thermal imaging techniques to measure plantar pressure and other foot parameters in diabetic patients. The system leverages pressure sensors, temperature sensors, and gait analysis to provide real-time data on plantar pressure distribution and potential risk areas. In this connection, many researchers have suggested a few techniques for early detection of DFUs. Their proposed works have been reviewed outlining the technological advancements in smart insole systems, their effectiveness in monitoring plantar pressure, and the application of machine learning for predictive analytics. The combination of machine learning models and thermal imaging has shown great potential in enhancing the accuracy of early DFU detection, improving patient outcomes, and reducing healthcare costs. This paper proposed a frame work and also discusses the different sensor types, methodologies, and design considerations for early diagnosis of diabetic foot ulcers using machine learning and thermal imaging techniques.