Characteristics of a multisensor system for non invasive glucose monitoring with external validation and prospective evaluation
| Autor: | A. Megej, Dominik Schaub, Roland E. Suri, Mark S. Talary, François Dewarrat, Jelena Klisic, Werner A. Stahel, Andreas Caduff, Martin Mueller, Pavel Zakharov, Marc Y. Donath |
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| Rok vydání: | 2011 |
| Předmět: |
Adult
Blood Glucose Biomedical Engineering Biophysics Prospective data Biosensing Techniques 02 engineering and technology 01 natural sciences Global model Prospective evaluation Diabetes mellitus Linear regression Electrochemistry medicine Humans business.industry Blood Glucose Self-Monitoring Type i diabetes mellitus 010401 analytical chemistry Non invasive External validation General Medicine Middle Aged 021001 nanoscience & nanotechnology medicine.disease 0104 chemical sciences Diabetes Mellitus Type 1 Glucose 0210 nano-technology business Nuclear medicine Biotechnology |
| Zdroj: | Biosensors & bioelectronics |
| ISSN: | 0956-5663 |
| Popis: | The Multisensor Glucose Monitoring System (MGMS) features non invasive sensors for dielectric characterisation of the skin and underlying tissue in a wide frequency range (1 kHz–100 MHz, 1 and 2 GHz) 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 ± 16 y; BMI 24.1 ± 1.3 kg/m2, duration of diabetes 27 ± 12 y; 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 51.9 mg dL−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. |
| Databáze: | OpenAIRE |
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