Abstract
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.
Highlights
Continuous glucose monitoring (CGM) sensors are portable devices that allow measuring and visualizing the glucose concentration almost continuously for several days
CGM sensors are composed of three main elements: (i) a needle-based sensor, which is usually inserted in the abdominal subcutis and measures an electrical signal proportional to the glucose concentration present in the interstitial fluid; (ii) a transmitter, which is applied over the sensor and is aimed at transmitting the signal; and (iii) a portable device, which receives the signal and visualizes it on a monitor
Thanks to the development and embedding of inter- and intra-day variability of the insulin sensitivity, the new version of the UVA/Padova Type 1 diabetes (T1D) simulator allows for generating physiological glucose profiles of T1D on multiple-day scenarios [54,55]; models of SMBG and CGM devices, able to reliably reproduce all the technological variability that can be observed in real life
Summary
Continuous glucose monitoring (CGM) sensors are portable devices that allow measuring and visualizing the glucose concentration almost continuously (usually every 1–5 min) for several days (so far up to seven days). As largely discussed in Sparacino et al [26], CGM sensors could be affected by lack of accuracy and reliability, which can negatively condition the performance of CGM-based applications and systems and limit their porting in clinical practice. For this reason, improving the performance of CGM sensors and the reliability of CGM data via suitable signal processing methods was identified as a key issue to be addressed. The aim of this paper is to review the past and present algorithmic challenges of CGM sensors, in order to to present how they have been tackled, with particular focus on the work done by our research group, and identify what we envision will be the possible future versions of CGM sensors
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