Zhang Yaguang, Sun Jingxue, Liu Liansheng, Qiao Hong
The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150086, China.
School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150080, China.
J Diabetes Complications. 2021 Aug;35(8):107929. doi: 10.1016/j.jdiacomp.2021.107929. Epub 2021 Apr 17.
Diabetes mellitus (DM) has become a serious illness in the whole world. Until now, there is no effective cure for patients with DM. It is well known that the glucose level is one key factor to determine the progress of DM. It is also an important reference to carry out the accurate and timely treatment for patients with DM. In this article, the related biosensors technology that can be utilized to identify and predict glucose level are reviewed in detail, including the algorithms that can help to achieve numerical value of glucose level. Firstly, the biosensor technology based on the physiological fluids are illustrated, including blood, sweat, interstitial fluid, ocular fluid, and other available fluids. Secondly, the algorithms for achieving numerical value of glucose level are investigated, including the physiological model-based method and the machine learning-based method. Finally, the future development trend and challenges of glucose level monitoring are given and the conclusions are drawn.
糖尿病(DM)已成为全球范围内的一种严重疾病。到目前为止,尚无针对糖尿病患者的有效治愈方法。众所周知,血糖水平是决定糖尿病病情发展的一个关键因素。它也是对糖尿病患者进行准确及时治疗的重要参考依据。在本文中,将详细综述可用于识别和预测血糖水平的相关生物传感器技术,包括有助于实现血糖水平数值的算法。首先,阐述基于生理体液的生物传感器技术,包括血液、汗液、间质液、眼液及其他可用体液。其次,研究实现血糖水平数值的算法,包括基于生理模型的方法和基于机器学习的方法。最后,给出血糖水平监测的未来发展趋势和挑战并得出结论。