Design and Implementation of a Multiparameter footwear system for Early Detection of Neuro- Ischemic Foot Complications

Diabetic foot wounds (DFWs) are the major complication of diabetes. They often leads delayed healing, recurring infections and in advanced stages, they may lead to partial or complete lower-limb amputations. This happens because diabetic neuropathy affects the patient ability to sense pain and early detection becomes hard. Meanwhile, currently employed diagnostic mechanisms including routine checks, thermal imaging, and pressure-monitoring insoles are expensive methods in terms of cost, employed not regularly hence few people each year, and used in an aggregate manner, meaning they cannot detect the multiplicity of risk factors at the same time. As a result, the wearable smart shoe can work simultaneously in all aspects. Smart shoes can combine force sensors to indicate abnormal pressure sensation, temperature sensors to signal overheat build-up, and sweat sensors to determine the complete moisture levels, all being part ulcer development. Similarly, an ESP32 microcontroller processes the sensor data using filtering algorithms and two alarms advised the user about a possible threat. Moreover, the automatic cooling module works when the heat or moisture levels increase, which eliminates the risk factors instead of giving the notifications. All in all, the technology addresses the essential problems of the existing designs by adding multimodal sensors, analytics in real-time, and passive cooling in the low-cost and convenient form of shoes. Overall, the proposed technique is intended to increase early detection accuracy, boost patient compliance, minimize the chance of ulcer formation, and eventually reduce diabetes-related healthcare expenses while increasing quality of life.