Design and manufacturing a smart shoe for diabetic foot ulcer monitoring and prediction system using internet-of-things technology

Prediction of diabetic foot ulcer outcome is helpful for clinicians in optimizing and individualizing management strategy. Diabetic foot ulcer (DFU) is one of the important complication of diabetes, which is occurred due to the destructive parameters in different locations of the foot. In order to decrease or prevent the formation of the diabetic foot ulcer at very early stages, we proposed in this paper an monitoring and control system using wirelessly controlled device that predicts the DFU before the occurrence; this system is designed for diabetic patients for daily monitoring, as it reduces frequent visits to the doctor and prevents complications that may include amputation or death in the worst cases and reduce the cost of treatment as well. A flexible insole is designed consisting of multiple type of non-invasive sensors, these sensors monitor different vital parameters (temperature, humidity, plantar pressure, and oxygen saturation in the blood), and these sensors are distributed on a flexible insole inside the shoe to monitor the sole of the foot. When these vital parameters exceed the threshold limit, the system sends an alert to the patient via a graphical user interface (GUI) using Internet-of-Things technology (IoT). It was found that the difference in temperature between the ulcerated foot as a result of high temperature and humidity and the healthy foot is 2.27 °C where it reached 38 °C, and the relative humidity values exceeded the normal limit to reach 74%. In the case of ulcers resulting from an increase in the values of plantar pressure on the foot and its recurrence, a decrease in the average values of oxygen saturation in the blood was observed, where its value decreased to 93.44%, where was the highest value of the plantar pressure 448.28 kpa. The system also demonstrated efficiency in response time and data processing speed, with a time delay of 1.5–2.5 s, depending on the Wi-Fi network's quality.