Retrospective Continuous-Time Blood Glucose Estimation in Free Living Conditions with a Non-Invasive Multisensor Device

Sensors

Mattia Zanon¹  Andreas Caduff¹  Andrea Facchinetti²  Giovanni Sparacino²  Giada Acciaroli² 

[1] Biovotion AG, 8008 Zurich, Switzerland;Department of Information Engineering, University of Padova, 35131 Padova, Italy;

关键词: diabetes;    continuous glucose monitoring;    non-invasive;    multisensor;   

DOI  :  10.3390/s19173677

来源: DOAJ

【 摘 要 】

Even if still at an early stage of development, non-invasive continuous glucose monitoring (NI-CGM) sensors represent a promising technology for optimizing diabetes therapy. Recent studies showed that the Multisensor provides useful information about glucose dynamics with a mean absolute relative difference (MARD) of 35.4% in a fully prospective setting. Here we propose a method that, exploiting the same Multisensor measurements, but in a retrospective setting, achieves a much better accuracy. Data acquired by the Multisensor during a long-term study are retrospectively processed following a two-step procedure. First, the raw data are transformed to a blood glucose (BG) estimate by a multiple linear regression model. Then, an enhancing module is applied in cascade to the regression model to improve the accuracy of the glucose estimation by retrofitting available BG references through a time-varying linear model. MARD between the retrospectively reconstructed BG time-series and reference values is 20%. Here, 94% of values fall in zone A or B of the Clarke Error Grid. The proposed algorithm achieved a level of accuracy that could make this device a potential complementary tool for diabetes management and also for guiding prediabetic or nondiabetic users through life-style changes.

【 授权许可】

Unknown