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Application of the continuous-discrete extended Kalman filter for fault detection in continuous glucose monitors for type 1 diabetes

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  • Zeinab Mahmoudi
  • Dimitri Boiroux
  • Morten Hagdrup
  • Kirsten Nørgaard
  • Niels Kjølstad Poulsen
  • Henrik Madsen
  • John Bagterp Jørgensen
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The purpose of this study is the online detection of faults and anomalies of a continuous glucose monitor (CGM). We simulated a type 1 diabetes patient using the Medtronic virtual patient model. The model is a system of stochastic differential equations and includes insulin pharmacokinetics, insulin-glucose interaction, and carbohydrate absorption. We simulated and detected two types of CGM faults, i.e., spike and drift. A fault was defined as a CGM value in any of the zones C, D, and E of the Clarke error grid analysis classification. Spike was modelled by a binomial distribution, and drift was modelled by a Gaussian random walk. We used a continuous-discrete extended Kalman filter for the fault detection, based on the statistical tests of the filter innovation and the 90-min prediction residuals of the sensor measurements. The spike detection had a sensitivity of 93% and a specificity of 100%. Also, the drift detection had a sensitivity of 80% and a specificity of 85%. Furthermore, with 100% sensitivity the proposed method was able to detect if the drift overestimates or underestimates the interstitial glucose concentration.

Original languageEnglish
Title of host publication2016 European Control Conference, ECC 2016
Number of pages6
PublisherInstitute of Electrical and Electronics Engineers Inc.
Publication date6 Jan 2017
Article number7810373
ISBN (Electronic)9781509025916
Publication statusPublished - 6 Jan 2017
Event2016 European Control Conference, ECC 2016 - Aalborg, Denmark
Duration: 29 Jun 20161 Jul 2016


Conference2016 European Control Conference, ECC 2016


2016 European Control Conference, ECC 2016


Aalborg, Denmark

Event: Conference

ID: 52336355