Bar-Ilan University, Faculty of Engineering, Ramat Gan, Israel, Israel.
Indian Institute of Technology (Indian School of Mines) Dhanbad, Department of Electronics Engineering, Dhanbad, Jharkhand, India, India.
J Biomed Opt. 2022 Sep;27(9). doi: 10.1117/1.JBO.27.9.097001.
The ability to perform frequent non-invasive monitoring of glucose in the bloodstream is very applicable for diabetic patients.
We experimentally verified a non-invasive multimode fiber-based technique for sensing glucose concentration in the bloodstream by extracting and analyzing the collected speckle patterns.
The proposed sensor consists of a laser source, digital camera, computer, multimode fiber, and alternating current (AC) generated magnetic field source. The experiments were performed using a covered (with cladding and jacket) and uncovered (without cladding and jacket) multimode fiber touching the skin under a magnetic field and without it. The subject's finger was placed on a fiber to detect the glucose concentration. The method tracks variations in the speckle patterns due to light interaction with the bloodstream affected by blood glucose.
The uncovered fiber placed above the finger under the AC magnetic field (150 G) at 140 Hz was found to have a lock-in amplification role, improving the glucose detection precision. The application of the machine learning algorithms in preprocessed speckle pattern data increase glucose measurement accuracy. Classification of the speckle patterns for uncovered fiber under the AC magnetic field allowed for detection of the blood glucose with high accuracy for all tested subjects compared with other tested configurations.
The proposed technique was theoretically analyzed and experimentally validated in this work. The results were verified by the traditional finger-prick method, which was also used for classification as a conventional reference marker of blood glucose levels. The main goal of the proposed technique was to develop a non-invasive, low-cost blood glucose sensor for easy use by humans.
能够频繁地无创监测血液中的葡萄糖水平，对糖尿病患者非常适用。
我们通过提取和分析采集到的散斑图案，实验验证了一种基于多模光纤的无创多模态技术，用于感测血液中的葡萄糖浓度。
所提出的传感器由激光源、数码相机、计算机、多模光纤和交流（AC）生成磁场源组成。实验使用覆盖（带有包层和护套）和未覆盖（没有包层和护套）的多模光纤在磁场下和没有磁场的情况下接触皮肤进行。将受测者的手指放在光纤上来检测葡萄糖浓度。该方法跟踪由于光与受血糖影响的血流相互作用而导致的散斑图案的变化。
在 140Hz 的 150G 交流磁场下，发现放置在手指上方的未覆盖光纤具有锁相放大作用，提高了葡萄糖检测精度。在预处理的散斑图案数据中应用机器学习算法可提高葡萄糖测量精度。与其他测试配置相比，对交流磁场下未覆盖光纤的散斑图案进行分类，可实现对所有受测者的高精度血糖检测。
在这项工作中，对所提出的技术进行了理论分析和实验验证。结果通过传统的指尖采血法进行了验证，该方法也被用作血糖水平的传统参考标记进行分类。所提出技术的主要目标是开发一种非侵入性、低成本的血糖传感器，便于人类使用。
