An Antenna Sensor for Noninvasive Blood Glucose Detection Based on Multiloop Complementary Split Ring

Microwave noninvasive blood glucose monitoring has garnered significant attention as an emerging technology in recent years. This article presents a novel multiring complementary split-ring resonator (CSRR) antenna sensor designed to enhance detection sensitivity and improve compactness. The proposed antenna sensor exhibits ideal resonances around 1.02, 1.79, and 2.23 GHz. A human forearm tissue simulation model was constructed to analyze the penetration capability and return loss of electromagnetic waves within the tissue at different frequencies under loaded and unloaded conditions. The study included both simulated and experimental validation of blood glucose detection performance. Additionally, three different machine learning regression models were employed to estimate blood glucose concentrations. Results indicate that electromagnetic waves can reach the target layer at various frequency points, and changes in blood glucose concentration result in variations in return loss amplitude and resonance frequency. The highest blood glucose detection sensitivity achieved was 1.29 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$ {10}^{-3}$ </tex-math></inline-formula> dB/(mg/dL) and 8.58 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$ {10}^{-3}$ </tex-math></inline-formula> MHz/(mg/dL). The coefficient of determination (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula>) for the gradient boosting decision tree (GBDT) regression model exceeded 98.2%. These findings suggest that the proposed antenna sensor holds significant potential for applications in the field of diabetes management.