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April 11, 2026Electronics2 citationsOpen Access

A Dual-Form Spiral-like Microwave Sensor for Non-Invasive Glucose Monitoring: From Planar Design to Wearable Implementation

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ZHZaid A. Abdul HassainMFMalik J. FarhanTETaha A. Elwi

Key Points

  • The aim is to develop a dual-form microwave sensor for accurate non-invasive glucose monitoring.
  • Proposed a compact spiral-like microwave resonator for glucose sensing.
  • Developed a full electromagnetic model to predict resonance behavior and validated with CST simulations.
  • Transformed the sensor into a flexible form for better skin contact and conformability.
  • Evaluated the sensor's sensitivity at various frequencies, assessing its performance under deformation.
  • Achieved glucose sensitivity of 0.05 dB/mg/dL at 10.1 GHz and 0.038 dB/mg/dL at 6.22 GHz.
  • Demonstrated a clear correlation between reflection magnitude and glucose level with R > 0.99.
  • Successfully validated deep learning framework, reducing RMSE to 0.28 mg/dL and MARD to 0.13%.
  • Ensured predictions fell within the <5% ISO-like risk region for clinical reliability.

Abstract

In this paper, a novel multiband microwave resonator is proposed and investigated for non-invasive glucose sensing applications. The structure is based on a compact, planar spiral-like geometry fed by a Coplanar waveguide (CPW) transmission line, designed to support multiple resonant modes through nested concentric rings. A full electromagnetic model was developed to predict the resonance behavior analytically, achieving excellent agreement with Computer Simulated Technology (CST) simulations across four resonant frequencies (2.7, 6.44, 8.0, and 12.8 GHz). The sensor demonstrated high glucose sensitivity at multiple frequencies, with peak values reaching 0.05 dB/mg/dL and 0.038 dB/mg/dL at 10.1 GHz and 6.22 GHz, respectively. To enhance conformability and skin contact, the antenna was further transformed into a semi-cylindrical flexible form suitable for finger-wrapping. Despite the mechanical deformation, the structure preserved its resonance while offering enhanced near-field interaction with biological tissues. The folded sensor achieved a sensitivity of 0.032 dB/mg/dL at 5.25 GHz and a peak gain of 6.05 dB, validating its robustness for wearable deployment. The clear correlation between reflection magnitude and glucose level (with R > 0.99) confirms the sensor’s potential as a passive, multiband, and non-invasive glucose monitoring platform. The physics-informed residual deep learning framework significantly enhances prediction accuracy, achieving an RMSE of 0.28 mg/dL, MARD of 0.13%, and confining 100% of both training and holdout predictions within the <5% ISO-like risk region, thereby ensuring robust and clinically reliable non-invasive glucose estimation.

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Cite This Study

Hassain et al. (2026) studied this question.

synapsesocial.com/papers/69d9e58f78050d08c1b75d6chttps://doi.org/10.3390/electronics15081567
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