Facchinetti Andrea
Department of Information Engineering, University of Padova, Padova 35131, Italy.
Sensors (Basel). 2016 Dec 9;16(12):2093. doi: 10.3390/s16122093.
Continuous glucose monitoring (CGM) sensors are portable devices that allow measuring and visualizing the glucose concentration in real time almost continuously for several days and are provided with hypo/hyperglycemic alerts and glucose trend information. CGM sensors have revolutionized Type 1 diabetes (T1D) management, improving glucose control when used adjunctively to self-monitoring blood glucose systems. Furthermore, CGM devices have stimulated the development of applications that were impossible to create without a continuous-time glucose signal, e.g., real-time predictive alerts of hypo/hyperglycemic episodes based on the prediction of future glucose concentration, automatic basal insulin attenuation methods for hypoglycemia prevention, and the artificial pancreas. However, CGM sensors' lack of accuracy and reliability limited their usability in the clinical practice, calling upon the academic community for the development of suitable signal processing methods to improve CGM performance. The aim of this paper is to review the past and present algorithmic challenges of CGM sensors, to show how they have been tackled by our research group, and to identify the possible future ones.
连续血糖监测（CGM）传感器是一种便携式设备，能够在数天内几乎持续实时测量并可视化血糖浓度，并具备低血糖/高血糖警报以及血糖趋势信息。CGM传感器彻底改变了1型糖尿病（T1D）的管理方式，在与自我血糖监测系统联合使用时可改善血糖控制。此外，CGM设备还推动了一些应用的发展，这些应用如果没有连续的血糖信号是无法创建的，例如基于未来血糖浓度预测的低血糖/高血糖发作实时预测警报、预防低血糖的自动基础胰岛素减量方法以及人工胰腺。然而，CGM传感器缺乏准确性和可靠性限制了它们在临床实践中的可用性，这促使学术界开发合适的信号处理方法来提高CGM的性能。本文旨在回顾CGM传感器过去和当前的算法挑战，展示我们的研究团队是如何应对这些挑战的，并确定未来可能出现的挑战。
