一种双针金银电极连续血糖监测装置

IF 5.6 4区 医学 Q1 ENGINEERING, BIOMEDICAL Irbm Pub Date : 2023-06-01 DOI:10.1016/j.irbm.2023.100752
C. Ben Ali Hassine , A. Tekin
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引用次数: 0

摘要

目的糖尿病是一种严重的长期疾病,使用连续血糖监测传感器可以减少对其他疼痛的侵入性血液检测方法的依赖,如手指血糖检测。根据我们的工作,基于电化学测量技术开发了一种低成本的连续葡萄糖传感器。材料传感器基于双针系统;金电极和银电极被集成到圆形电子印刷电路板(PCB)中。传感部分基于生物电化学测量。葡萄糖氧化酶(Gox)作为活性传感元件,二茂铁(Fc)作为介质。使用了简单和低成本的涂层方法;这些方法是自组装单层和深涂层。这将降低传感器的最终成本,因为没有使用昂贵的技术。电气子系统包含一个低噪声、低功耗的跨阻抗前端,以及一个带12位模数转换器(ADC)的单芯片低功耗蓝牙微控制器。作为初步体外实验的结果,给出了详细的分析性能指标。该装置在0-400 mg/dl的线性范围内始终显示出3.059 mV/(mg/dl)的灵敏度读数。结论所提出的研究在葡萄糖检测方面显示出了有希望的结果。因此,经过进一步的研究和分析,这种类型的传感器可以用于针对生物学应用的不同分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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A Double-Needle Gold-Silver Electrodes Continuous Glucose Monitoring Device

Objectives

Diabetes is a serious, long-term disease and the use of continuous glucose monitoring sensors can reduce reliance on other painful invasive blood testing methods such as the finger blood glucose test. According to our work, a low-cost continuous glucose sensor has been developed based on electrochemical measurement techniques.

Materials

The sensor is based on a two needles system; a gold and a silver electrode are integrated into a circular shaped electronic printed circuit board (PCB). The sensing part is based on biological electrochemical measurements. Glucose oxidase (Gox) was used as the active sensing element and ferrocene (Fc) as a mediator. Simple and low-cost coating methods were used; these methods are self-assembled monolayers and deep coating. This will reduce the final cost of the sensor as no expensive technique was used. The electrical subsystem contains a low-noise and low-power trans-impedance front-end as well as a single-chip low-power Bluetooth microcontroller with a 12-bit Analog-to-Digital Converter (ADC).

Results

The sensor was tested in various concentrations of glucose. As a result of initial in vitro experiments, detailed analytical performance metrics are presented. The device has consistently shown a sensitivity of 3.059 mV/(mg/dl) reading with a linear range of 0-400 mg/dl.

Conclusion

The proposed study shows promising results for glucose detection. Thus, this type of sensor can be used for different analyzes targeting biological applications after further investigations and analysis.

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来源期刊
Irbm
Irbm ENGINEERING, BIOMEDICAL-
CiteScore
10.30
自引率
4.20%
发文量
81
审稿时长
57 days
期刊介绍: IRBM is the journal of the AGBM (Alliance for engineering in Biology an Medicine / Alliance pour le génie biologique et médical) and the SFGBM (BioMedical Engineering French Society / Société française de génie biologique médical) and the AFIB (French Association of Biomedical Engineers / Association française des ingénieurs biomédicaux). As a vehicle of information and knowledge in the field of biomedical technologies, IRBM is devoted to fundamental as well as clinical research. Biomedical engineering and use of new technologies are the cornerstones of IRBM, providing authors and users with the latest information. Its six issues per year propose reviews (state-of-the-art and current knowledge), original articles directed at fundamental research and articles focusing on biomedical engineering. All articles are submitted to peer reviewers acting as guarantors for IRBM''s scientific and medical content. The field covered by IRBM includes all the discipline of Biomedical engineering. Thereby, the type of papers published include those that cover the technological and methodological development in: -Physiological and Biological Signal processing (EEG, MEG, ECG…)- Medical Image processing- Biomechanics- Biomaterials- Medical Physics- Biophysics- Physiological and Biological Sensors- Information technologies in healthcare- Disability research- Computational physiology- …
期刊最新文献
Editorial Board Contents Potential of Near-Infrared Optical Techniques for Non-invasive Blood Glucose Measurement: A Pilot Study Corrigendum to “Automatic Detection of Severely and Mildly Infected COVID-19 Patients with Supervised Machine Learning Models” [IRBM (2023) 100725] Comprehensive Review of Feature Extraction Techniques for sEMG Signal Classification: From Handcrafted Features to Deep Learning Approaches
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