Characteristics of a multisensor system for non invasive glucose monitoring with external validation and prospective evaluation

Caduff, A. and Mueller, M. and Megej, A. and Dewarrat, F. and Suri, R. E. and Klisic, J. and Donath, M. and Zakharov, P. and Schaub, D. and Stahel, W. A. and Talary, M. S.. (2011) Characteristics of a multisensor system for non invasive glucose monitoring with external validation and prospective evaluation. Biosensors & bioelectronics, Vol. 26, H. 9. pp. 3794-3800.

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Official URL: http://edoc.unibas.ch/dok/A6338607

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The Multisensor Glucose Monitoring System (MGMS) features non invasive sensors for dielectric characterisation of the skin and underlying tissue in a wide frequency range (1kHz-100MHz, 1 and 2GHz) as well as optical characterisation. In this paper we describe the results of using an MGMS in a miniaturised housing with fully integrated sensors and battery. Six patients with Type I Diabetes Mellitus (age 44+/-16y; BMI 24.1+/-1.3kg/m(2), duration of diabetes 27+/-12y; HbA1c 7.3+/-1.0%) wore a single Multisensor at the upper arm position and performed a total of 45 in-clinic study days with 7 study days per patient on average (min. 5 and max. 10). Glucose changes were induced either orally or by i.v. glucose administration and the blood glucose was measured routinely. Several prospective data evaluation routines were applied to evaluate the data. The results are shown using one of the restrictive data evaluation routines, where measurements from the first 22 study days were used to train a linear regression model. The global model was then prospectively applied to the data of the remaining 23 study days to allow for an external validation of glucose prediction. The model application yielded a Mean Absolute Relative Difference of 40.8%, a Mean Absolute Difference of 51.9mgdL(-1), and a correlation of 0.84 on average per study day. The Clarke error grid analyses showed 89.0% in A+B, 4.5% in C, 4.6% in D and 1.9% in the E region. Prospective application of a global, purely statistical model, demonstrates that glucose variations can be tracked non invasively by the MGMS in most cases under these conditions.
Faculties and Departments:03 Faculty of Medicine > Departement Biomedizin > Department of Biomedicine, University Hospital Basel > Diabetes Research (Donath)
UniBasel Contributors:Donath, Marc
Item Type:Article, refereed
Article Subtype:Research Article
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:10 Apr 2015 09:13
Deposited On:10 Apr 2015 09:13

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