Electrical and Computer Engineering, University of Alberta, 116 St., Edmonton, T6G 2R3, AB, Canada.
University of Toronto, 10 King's College Rd, Toronto, M5S 3G4, ON, Canada.
Biosens Bioelectron. 2023 Dec 1;241:115668. doi: 10.1016/j.bios.2023.115668. Epub 2023 Sep 14.
Continuous glucose monitoring schemes that avoid finger pricking are of utmost importance to enhance the comfort and lifestyle of diabetic patients. To this aim, we propose a microwave planar sensing platform as a potent sensing technology that extends its applications to biomedical analytes. In this paper, a compact planar resonator-based sensor is introduced for noncontact sensing of glucose. Furthermore, in vivo and in-vitro tests using a microfluidic channel system and in clinical trial settings demonstrate its reliable operation. The proposed sensor offers real-time response and a high linear correlation (R ∼ 0.913) between the measured sensor response and the blood glucose level (GL). The sensor is also enhanced with machine learning to predict the variation of body glucose levels for non-diabetic and diabetic patients. This addition is instrumental in triggering preemptive measures in cases of unusual glucose level trends. In addition, it allows for the detection of common artifacts of the sensor as anomalies so that they can be removed from the measured data. The proposed system is designed to noninvasively monitor interstitial glucose levels in humans, introducing the opportunity to create a customized wearable apparatus with the ability to learn.
避免手指穿刺的连续血糖监测方案对于提高糖尿病患者的舒适度和生活方式至关重要。为此，我们提出了一种微波平面传感平台作为一种强大的传感技术，将其应用扩展到生物医学分析物。在本文中，介绍了一种基于紧凑平面谐振器的传感器，用于非接触式葡萄糖传感。此外，使用微流道系统进行的体内和体外测试以及临床试验环境证明了其可靠的操作。所提出的传感器具有实时响应和测量传感器响应与血糖水平(GL)之间的高线性相关性（R∼0.913）。该传感器还通过机器学习进行了增强，以预测非糖尿病和糖尿病患者的血糖水平变化。这一增强功能有助于在血糖水平异常趋势的情况下采取先发制人的措施。此外，它还可以检测传感器的常见伪影作为异常，以便从测量数据中删除它们。该系统旨在非侵入性地监测人体间质葡萄糖水平，为创建具有学习能力的定制可穿戴设备提供了机会。
