Next Article in Journal
Impacts of Satellite Orbit and Clock on Real-Time GPS Point and Relative Positioning
Previous Article in Journal
The Development of Indicator Cotton Swabs for the Detection of pH in Wounds
Article Menu
Issue 6 (June) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(6), 1361; doi:10.3390/s17061361

Modeling the Error of the Medtronic Paradigm Veo Enlite Glucose Sensor

1
Institut d’Informàtica i Aplicacions, Universitat de Girona, Campus de Montilivi, s/n, Edifici P4, 17071 Girona, Spain
2
Federal University of Technology—Paraná, 85053-252 Guarapuava, Brazil
3
Department of Information Engineering, University of Padova, 35131 Padova, Italy
4
Service of Diabetes, Endocrinology and Nutrition (UDEN), Institut d’Investigació Biomédica de Girona (IdIBGi), Avinguda de França s/n, 17007 Girona, Spain
5
CIBER Pathophysiology of Obesity and Nutrition, Instituto de Salud Carlos III, 28029 Madrid, Spain
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Huangxian Ju
Received: 24 March 2017 / Revised: 16 May 2017 / Accepted: 3 June 2017 / Published: 12 June 2017
(This article belongs to the Section Biosensors)
View Full-Text   |   Download PDF [545 KB, uploaded 12 June 2017]   |  

Abstract

Continuous glucose monitors (CGMs) are prone to inaccuracy due to time lags, sensor drift, calibration errors, and measurement noise. The aim of this study is to derive the model of the error of the second generation Medtronic Paradigm Veo Enlite (ENL) sensor and compare it with the Dexcom SEVEN PLUS (7P), G4 PLATINUM (G4P), and advanced G4 for Artificial Pancreas studies (G4AP) systems. An enhanced methodology to a previously employed technique was utilized to dissect the sensor error into several components. The dataset used included 37 inpatient sessions in 10 subjects with type 1 diabetes (T1D), in which CGMs were worn in parallel and blood glucose (BG) samples were analyzed every 15 ± 5 min Calibration error and sensor drift of the ENL sensor was best described by a linear relationship related to the gain and offset. The mean time lag estimated by the model is 9.4 ± 6.5 min. The overall average mean absolute relative difference (MARD) of the ENL sensor was 11.68 ± 5.07% Calibration error had the highest contribution to total error in the ENL sensor. This was also reported in the 7P, G4P, and G4AP. The model of the ENL sensor error will be useful to test the in silico performance of CGM-based applications, i.e., the artificial pancreas, employing this kind of sensor. View Full-Text
Keywords: continuous glucose monitor; artificial pancreas; type 1 diabetes; sensor error; measurement noise; calibration error; enlite sensor continuous glucose monitor; artificial pancreas; type 1 diabetes; sensor error; measurement noise; calibration error; enlite sensor
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Biagi, L.; Ramkissoon, C.M.; Facchinetti, A.; Leal, Y.; Vehi, J. Modeling the Error of the Medtronic Paradigm Veo Enlite Glucose Sensor. Sensors 2017, 17, 1361.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top