Next-Gen Non-Invasive Glucose Monitoring Using Microwave Sensors and AI-Based Thumb Positioning Analysis

Because of discomfort and accuracy problems, the existing non-invasive glucose monitoring devices include optical sensors and finger-prick tests have long been under doubt for their viability. Variations in skin type and environmental interference might make these techniques unreliable. To get past these constraints, the study presents a fresh approach combining artificial intelligence (AI)-based thumb positioning analysis with microwave sensors. By spotting changes in the dielectric characteristics of the skin brought on by glucose, the microwave sensors offer exact, invasive, real-time readings. Through best sensor alignment, AI removes thumb position errors. Performance assessment indicates substantially better outcomes than the existing systems with an R2 of 0.98, RMSE of 7.1 mg/dL, and MAE of 5.2 mg/dL. The great flexibility of the proposed system to a wide spectrum of demographics and excellent user compliance (95%) underlines its possibility for efficient and comfortable diabetes control. The technique represents a substantial development in non-invasive glucose monitoring.