Development and Evaluation of a sensor-based Non-Invasive Blood Glucose Monitoring System using Near-Infrared Spectroscopy

Diabetes Mellitus is a significant global health issue, affecting over half a billion people worldwide. Current glucose monitoring methods are invasive, painful, and require skilled application, highlighting the need for development of effective, non-invasive, and easy to use methods. This paper presents our work on the design, development, and evaluation of a non-invasive blood glucose monitoring system, utilizing Near-Infrared Spectroscopy technique for glucose monitoring. The proposed system comprises of MAX30102 biosensor connected to an ESP32 microcontroller. The biosensor captures the photoplethysmogram signals, which are then processed by a microcontroller to evaluate blood glucose level. In order to increase the accuracy of the results, we have incorporated linear regression with Clarke error grid analysis to calibrate our system. The linear regression model is trained by comparing the results obtained through the developed system with that of commercial-off-the-self invasive device. The glucose levels obtained through the developed system are displayed in real-time on an Organic LED (OLED) screen and uploaded to a cloud server via Internet of Things (IoT) for remote monitoring. To validate the performance of the proposed system, we have compared the performance metrics of our system against existing solutions published in the literature. Performance comparison show that our system achieves a reasonably good accuracy with a root mean square error of 13.8 mg/dl and a mean absolute relative difference of 12%. The proposed system offers a painless, reliable, and convenient solution, potentially improving glucose monitoring for patients worldwide.