Abstract
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.
Highlights
IntroductionNon-invasive continuous glucose monitoring (NI-CGM) has been widely investigated in the last years [1,2,3,4,5] because it would obviously represent an appealing technology to monitor glucose changes with no discomfort related to the use of subcutaneous needles [6,7,8] or implantable devices [6]. in terms of accuracy and reliability, the performance of NI-CGM is still far from that of commercial minimally-invasive CGM sensors, some encouraging results have been demonstrated in strictly controlled conditions during in-clinic sessions [5,9,10,11]
In the present study we assessed the accuracy of a multisensor device for Non-invasive continuous glucose monitoring (NI-CGM) in the less challenging, but still useful application, of retrospective, off-line, blood glucose (BG) estimation
We proposed a two-step procedure in which, at step 1, the Multisensor measurements were combined into a BG
Summary
Non-invasive continuous glucose monitoring (NI-CGM) has been widely investigated in the last years [1,2,3,4,5] because it would obviously represent an appealing technology to monitor glucose changes with no discomfort related to the use of subcutaneous needles [6,7,8] or implantable devices [6]. in terms of accuracy and reliability, the performance of NI-CGM is still far from that of commercial minimally-invasive CGM sensors, some encouraging results have been demonstrated in strictly controlled conditions during in-clinic sessions [5,9,10,11]. Non-invasive continuous glucose monitoring (NI-CGM) has been widely investigated in the last years [1,2,3,4,5] because it would obviously represent an appealing technology to monitor glucose changes with no discomfort related to the use of subcutaneous needles [6,7,8] or implantable devices [6]. The use of NI-CGM technology in uncontrolled conditions met in daily life has shown several critical aspects, mostly related to the influence of external perturbations, e.g., environmental factors and non-glucose related physiological confounders that influence the sensor measurements [10,11,12,13,14,15]. Solianis Monitoring AG (Zurich, Switzerland) acquired by Biovotion AG (Zurich, Switzerland), proposed and developed a multisensor
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