Sensitivity Approach for Blood Glucose Impedance Data Using the Geselowitz Theorem

IF 5.4 Q1 CHEMISTRY, ANALYTICAL Sensing and Bio-Sensing Research Pub Date : 2024-09-26 DOI:10.1016/j.sbsr.2024.100698
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Abstract

The article presents a preclinical study focused on developing a non-invasive blood glucose monitoring device. Current glucose monitoring methods, such as capillary or venous tests, are inconvenient for frequent use, making continuous monitoring challenging. This study explores the BGP (Bruna Gabriela Pedro) model, which links electrical impedance to blood glucose levels, as a potential alternative. Using the Geselowitz Theorem and impedance spectroscopy in a 4-electrode configuration, the study investigates the relationship between blood conductivity and glucose concentration. Impedance spectra were recorded for five human blood samples with glucose concentrations between 106 and 188 mg/dL. These samples were housed in an insulating container with four stainless steel electrodes. Conductivity was calculated using the Geselowitz Theorem at 1.0, 3.9, and 24.9 kHz. A finite element model built in COMSOL was employed to assess electrode sensitivity, which had a maximum regression error of 3.75 %. The results demonstrated a sigmoid relationship between blood glucose concentration and conductivity, with impedance decreasing non-linearly as glucose levels increased. Sensitivity diminished for glucose concentrations exceeding 188 mg/dL. An increase of 82 mg/dL in glucose concentration led to conductivity changes of 1.14, 2.82, and 5.14 S/m at frequencies of 1.0, 3.9, and 24.9 kHz, respectively. The findings suggest that the BGP analytical model could be refined through the inclusion of additional data on glucose's impact on electrical impedance. These improvements could support the development of non-invasive glucose meters. The research holds significant clinical potential for the creation of a simple, cost-effective glucose monitoring device. Continuous glucose monitoring could enhance diagnostic accuracy and support better therapeutic decision-making, particularly in emergency care. The affordability and accessibility of such a device may benefit a broad patient base.
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利用格塞洛维茨定理的血糖阻抗数据灵敏度方法
文章介绍了一项临床前研究,重点是开发一种无创血糖监测设备。目前的血糖监测方法,如毛细血管或静脉测试,不方便经常使用,使得连续监测具有挑战性。本研究探讨了 BGP(Bruna Gabriela Pedro)模型,该模型将电阻抗与血糖水平联系起来,可作为一种潜在的替代方法。该研究利用格塞洛维茨定理和 4 个电极配置的阻抗谱,研究了血液电导率与葡萄糖浓度之间的关系。研究人员记录了葡萄糖浓度在 106 至 188 mg/dL 之间的五个人体血液样本的阻抗光谱。这些样本被放置在一个带有四个不锈钢电极的绝缘容器中。在 1.0、3.9 和 24.9 kHz 频率下,使用格塞洛维茨定理计算电导率。采用 COMSOL 建立的有限元模型评估电极灵敏度,其最大回归误差为 3.75%。结果表明,血糖浓度与电导率之间呈弧形关系,阻抗随血糖水平的升高而非线性下降。葡萄糖浓度超过 188 毫克/分升时,灵敏度降低。葡萄糖浓度每增加 82 毫克/分升,在频率为 1.0、3.9 和 24.9 千赫时,电导率的变化分别为 1.14、2.82 和 5.14 S/m。研究结果表明,可以通过加入更多有关葡萄糖对电阻抗影响的数据来改进 BGP 分析模型。这些改进将有助于无创血糖仪的开发。这项研究具有巨大的临床潜力,可用于制造简单、经济的葡萄糖监测设备。连续葡萄糖监测可以提高诊断的准确性,支持更好的治疗决策,特别是在急救护理中。这种设备价格低廉,使用方便,可使广大患者受益。
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来源期刊
Sensing and Bio-Sensing Research
Sensing and Bio-Sensing Research Engineering-Electrical and Electronic Engineering
CiteScore
10.70
自引率
3.80%
发文量
68
审稿时长
87 days
期刊介绍: Sensing and Bio-Sensing Research is an open access journal dedicated to the research, design, development, and application of bio-sensing and sensing technologies. The editors will accept research papers, reviews, field trials, and validation studies that are of significant relevance. These submissions should describe new concepts, enhance understanding of the field, or offer insights into the practical application, manufacturing, and commercialization of bio-sensing and sensing technologies. The journal covers a wide range of topics, including sensing principles and mechanisms, new materials development for transducers and recognition components, fabrication technology, and various types of sensors such as optical, electrochemical, mass-sensitive, gas, biosensors, and more. It also includes environmental, process control, and biomedical applications, signal processing, chemometrics, optoelectronic, mechanical, thermal, and magnetic sensors, as well as interface electronics. Additionally, it covers sensor systems and applications, µTAS (Micro Total Analysis Systems), development of solid-state devices for transducing physical signals, and analytical devices incorporating biological materials.
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