ArticlePloS one2022
Glucose level detection using millimetre-wave metamaterial-inspired resonator.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- A Multifrequency Millimeter-Wave CMOS Sensor for Non-Invasive Continuous Glucose Monitoring Using UMC 0.18 μm Technology.Biosensors · 2026Article
- Machine learning-assisted optimization of a terahertz photonic metamaterial absorber for blood cancer detection.PloS one · 2026Article
- Electromagnetically Coupled Resonant Face-to-Face Double-Layer Metamaterial for Highly Sensitive THz Impedance Spectroscopy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
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9 authors.
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Abstract
Millimetre-wave frequencies are promising for sensitive detection of glucose levels in the blood, where the temperature effect is insignificant. All these features provide the feasibility of continuous, portable, and accurate monitoring of glucose levels. This paper presents a metamaterial-inspired resonator comprising five split-rings to detect glucose levels at 24.9 GHz. The plexiglass case containing blood is modelled on the sensor's surface and the structure is simulated for the glucose levels in blood from 50 mg/dl to 120 mg/dl. The novelty of the sensor is demonstrated by the capability to sense the normal glucose levels at millimetre-wave frequencies. The dielectric characteristics of the blood are modelled by using the Debye parameters. The proposed design can detect small changes in the dielectric properties of blood caused by varying glucose levels. The variation in the transmission coefficient for each glucose level tested in this study is determined by the quality factor and resonant frequency. The sensor presented can detect the change in the quality factor of transmission response up to 2.71/mg/dl. The sensor's performance has also been tested to detect diabetic hyperosmolar syndrome. The sensor showed a linear shift in resonant frequency with the change in glucose levels, and an R2 of 0.9976 was obtained by applying regression analysis. Thus, the sensor can be used to monitor glucose in a normal range as well as at extreme levels.
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