Computational Mechanics, Faculty of Mechanical Engineering, Otto Von Guericke University Magdeburg, Universitätsplatz 2, 39106 Magdeburg, Germany.
Faculty of Technical Engineering, Tartous University, Tartous P.O. Box 2147, Syria.
Biosensors (Basel). 2023 Nov 20;13(11):991. doi: 10.3390/bios13110991.
Diabetes mellitus (DM) is a chronic metabolic condition characterized by high blood glucose levels owing to decreased insulin production or sensitivity. Current diagnostic approaches for gestational diabetes entail intrusive blood tests, which are painful and impractical for regular monitoring. Additionally, typical blood glucose monitoring systems are restricted in their measurement frequency and need finger pricks for blood samples. This research study focuses on the development of a non-invasive, real-time glucose monitoring method based on the detection of glucose in human tears and finger blood using mid-infrared (IR) spectroscopy. The proposed solution combines a fuzzy logic-based calibration mechanism with an IR sensor and Arduino controller. This calibration technique increases the accuracy of non-invasive glucose testing based on MID absorbance in fingertips and human tears. The data demonstrate that our device has high accuracy and reliability, with an error rate of less than 3%, according to the EGA. Out of 360 measurements, 97.5% fell into zone A, 2.2% into zone B, and 0.3% into zone C of the Clarke Error Grid. This suggests that our device can give clinically precise and acceptable estimates of blood glucose levels without inflicting any harm or discomfort on the user.
糖尿病（DM）是一种慢性代谢性疾病，其特征是由于胰岛素产生或敏感性降低而导致的高血糖水平。目前用于诊断妊娠糖尿病的方法需要进行侵入性血液检测，这既痛苦又不适合常规监测。此外，典型的血糖监测系统在测量频率上受到限制，并且需要用手指刺破取血样。本研究旨在开发一种基于中红外（IR）光谱检测人泪和手指血中葡萄糖的非侵入性、实时血糖监测方法。所提出的解决方案结合了基于模糊逻辑的校准机制与 IR 传感器和 Arduino 控制器。该校准技术提高了基于指尖和人泪中的 MID 吸光度的非侵入性葡萄糖测试的准确性。根据 EGA，数据表明我们的设备具有高精度和高可靠性，误差率小于 3%。在 360 次测量中，97.5%落在 Clarke 误差网格的 A 区，2.2%落在 B 区，0.3%落在 C 区。这表明我们的设备可以提供精确且可接受的临床估计血糖水平，而不会对用户造成任何伤害或不适。
