Sensitivity-Enhanced Fluidic Glucose Sensor Based on a Microwave Resonator Coupled With an Interferometric System for Noninvasive and Continuous Detection

Jang, Chorom; Park, Jin Kwan; Lee, Heejo; Yun, Gi-Ho; Yook, Jong‐Gwan

doi:10.1109/tbcas.2021.3112744

Cited by 22 publications

(11 citation statements)

References 59 publications

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“…In the implementation of CSRR-based sensors, a microfluidic channel chip should be placed on the ground plane to allow liquid injection. However, the applications of planar microwave sensors usually require an additional periphery readout circuitry [ 17 , 18 ]. The assembly of the microfluidic channel chip on the ground plane would make the CSRR-based sensors difficult to integrate with the periphery circuitry.…”

Section: Introductionmentioning

confidence: 99%

An Improved Split-Ring Resonator-Based Sensor for Microfluidic Applications

Wang

et al. 2022

Sensors

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This study proposes an ultrahigh-sensitivity split-ring resonator-based microwave sensor for retrieving the complex permittivity of liquid samples. An interdigital capacitor structure was used to expand the sensing area and the sensitivity. A defected ground structure and A parallel dual split-ring resonator were introduced to improve the quality factor. A polydimethylsiloxane microfluidic channel substrate was placed above the interdigital capacitor structure. The channel route coincided with the interdigital gap to fully utilize the strong electric field. Ethanol–water solutions with varying ethanol fractions were injected into the channel as the testing liquid. It was demonstrated that the variation in resonant frequency can be used to retrieve the dielectric properties of liquid samples. The proposed sensor used a small liquid volume of ~0.68 μL and provided values in good agreement with the reference data.

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Section: Introductionmentioning

confidence: 99%

An Improved Split-Ring Resonator-Based Sensor for Microfluidic Applications

Wang

et al. 2022

Sensors

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“…This significantly depends on the chosen operating frequency, which defines the penetration depth. The working frequencies are mostly in the range of 0-6 GHz [32,92,[95][96][97]99,104,105,[138][139][140], and the others are in the range of 10-20 GHz [93,98]. In general, the higher the frequency, the lower the penetration depth.…”

Section: Non-invasive Sensor Principlesmentioning

confidence: 99%

“…For one person, nearly all values could be classified in A, whereas the results of another person with the same RNN had also values in the high risk zone D. Nevertheless, due to the small number of test persons (6), the reason for the deviation was not further investigated. In addition, resonator-based measurement systems were proposed by Jang et al [139] and Juan et al [161]. In [139], 100% of the sensor readings fell in zone A, whereas in [139] up to 93.11% were in zones A and B and 6.89% in zone D. Therefore, the results of [139] outperformed commercial sensors.…”

Section: Evaluation With Clarke Error Gridmentioning

confidence: 99%

“…In addition, resonator-based measurement systems were proposed by Jang et al [139] and Juan et al [161]. In [139], 100% of the sensor readings fell in zone A, whereas in [139] up to 93.11% were in zones A and B and 6.89% in zone D. Therefore, the results of [139] outperformed commercial sensors. However, the performance of the resonant-based sensor was evaluated with a DI water solution, which does not represent real conditions for non-invasive glucose sensing.…”

Section: Evaluation With Clarke Error Gridmentioning

confidence: 99%

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Commercial and Scientific Solutions for Blood Glucose Monitoring—A Review

Xue

Thalmayer

Zeising

et al. 2022

Sensors

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Diabetes is a chronic and, according to the state of the art, an incurable disease. Therefore, to treat diabetes, regular blood glucose monitoring is crucial since it is mandatory to mitigate the risk and incidence of hyperglycemia and hypoglycemia. Nowadays, it is common to use blood glucose meters or continuous glucose monitoring via stinging the skin, which is classified as invasive monitoring. In recent decades, non-invasive monitoring has been regarded as a dominant research field. In this paper, electrochemical and electromagnetic non-invasive blood glucose monitoring approaches will be discussed. Thereby, scientific sensor systems are compared to commercial devices by validating the sensor principle and investigating their performance utilizing the Clarke error grid. Additionally, the opportunities to enhance the overall accuracy and stability of non-invasive glucose sensing and even predict blood glucose development to avoid hyperglycemia and hypoglycemia using post-processing and sensor fusion are presented. Overall, the scientific approaches show a comparable accuracy in the Clarke error grid to that of the commercial ones. However, they are in different stages of development and, therefore, need improvement regarding parameter optimization, temperature dependency, or testing with blood under real conditions. Moreover, the size of scientific sensing solutions must be further reduced for a wearable monitoring system.

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“…Nowadays, improvements in sensor and signal processing are mostly of interest for researchers. Some reports designed advanced sensor models to improve the sensitivity [13,21]. Artificial intelligence has been used to process signals in diagnosis systems [22][23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Non-invasive, intelligent, and continuous monitoring of human blood glucose with UWB dual-antenna and cascade CNN

Wang

Xiao

Pang

et al. 2023

Meas. Sci. Technol.

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Long-term and frequent blood glucose detection by requiring finger-pick blood become unrealistic. An appropriate non-invasive detection system is thus highly desirable to deal better with it. In this paper, a non-invasive and intelligent dual-sensing system is reported. The feasibility of proposed system has been verified by glucose solution, animal serum and human trials. In the in-vivo experiments, detection signal has a high correlation (r = 0.96) with blood glucose level. An improved convolution neural network (cascade CNN) is purposed to be employed for estimation of blood glucose level (BGL). For the estimation results of BGL, the root mean squared error (RMSE) of 7.3217 mg/dL and mean absolute relative difference (MARD) of 4.7209% were achieved. The estimated results were also 100% fallen into the clinically acceptable zones of the Clarke error grid analysis, which indicated that proposed system could be potentially used for clinical measuring.

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Sensitivity-Enhanced Fluidic Glucose Sensor Based on a Microwave Resonator Coupled With an Interferometric System for Noninvasive and Continuous Detection

Cited by 22 publications

References 59 publications

An Improved Split-Ring Resonator-Based Sensor for Microfluidic Applications

An Improved Split-Ring Resonator-Based Sensor for Microfluidic Applications

Commercial and Scientific Solutions for Blood Glucose Monitoring—A Review

Non-invasive, intelligent, and continuous monitoring of human blood glucose with UWB dual-antenna and cascade CNN

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