Comparison of three nonlinear filters for fault detection in continuous glucose monitors.

Zeinab Mahmoudi; Sabrina Lyngbye Wendt; Dimitri Boiroux; Morten Hagdrup; Kirsten Norgaard; Niels Kjolstad Poulsen; Henrik Madsen; John Bagterp Jorgensen

doi:10.1109/EMBC.2016.7591484

Comparison of three nonlinear filters for fault detection in continuous glucose monitors.

Zeinab Mahmoudi, Sabrina Lyngbye Wendt, Dimitri Boiroux, Morten Hagdrup, Kirsten Norgaard, Niels Kjolstad Poulsen, Henrik Madsen, John Bagterp Jorgensen

Department of Endocrinology

8 Citations (Scopus)

Abstract

The purpose of this study is to compare the performance of three nonlinear filters in online drift detection of continuous glucose monitors. The nonlinear filters are the extended Kalman filter (EKF), the unscented Kalman filter (UKF), and the particle filter (PF). They are all based on a nonlinear model of the glucose-insulin dynamics in people with type 1 diabetes. Drift is modelled by a Gaussian random walk and is detected based on the statistical tests of the 90-min prediction residuals of the filters. The unscented Kalman filter had the highest average F score of 85.9%, and the smallest average detection delay of 84.1%, with the average detection sensitivity of 82.6%, and average specificity of 91.0%.

Original language	English
Journal	Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
Volume	2016
Pages (from-to)	3507-3510
Number of pages	4
ISSN	2375-7477
DOIs	https://doi.org/10.1109/EMBC.2016.7591484
Publication status	Published - 2016

Keywords

Blood Chemical Analysis
Blood Glucose
Humans
Models, Biological
Nonlinear Dynamics
Normal Distribution
Signal Processing, Computer-Assisted
Comparative Study
Journal Article
Research Support, Non-U.S. Gov't

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10.1109/EMBC.2016.7591484

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Mahmoudi, Z., Wendt, S. L., Boiroux, D., Hagdrup, M., Norgaard, K., Poulsen, N. K., Madsen, H., & Jorgensen, J. B. (2016). Comparison of three nonlinear filters for fault detection in continuous glucose monitors. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, 2016, 3507-3510. https://doi.org/10.1109/EMBC.2016.7591484

Comparison of three nonlinear filters for fault detection in continuous glucose monitors. / Mahmoudi, Zeinab; Wendt, Sabrina Lyngbye; Boiroux, Dimitri et al.
In: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, Vol. 2016, 2016, p. 3507-3510.

Research output: Contribution to journal › Conference article › Research › peer-review

Mahmoudi, Z, Wendt, SL, Boiroux, D, Hagdrup, M, Norgaard, K, Poulsen, NK, Madsen, H & Jorgensen, JB 2016, 'Comparison of three nonlinear filters for fault detection in continuous glucose monitors.', Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, vol. 2016, pp. 3507-3510. https://doi.org/10.1109/EMBC.2016.7591484

Mahmoudi Z, Wendt SL, Boiroux D, Hagdrup M, Norgaard K, Poulsen NK et al. Comparison of three nonlinear filters for fault detection in continuous glucose monitors. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference. 2016;2016:3507-3510. doi: 10.1109/EMBC.2016.7591484

Mahmoudi, Zeinab ; Wendt, Sabrina Lyngbye ; Boiroux, Dimitri et al. / Comparison of three nonlinear filters for fault detection in continuous glucose monitors. In: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference. 2016 ; Vol. 2016. pp. 3507-3510.

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abstract = "The purpose of this study is to compare the performance of three nonlinear filters in online drift detection of continuous glucose monitors. The nonlinear filters are the extended Kalman filter (EKF), the unscented Kalman filter (UKF), and the particle filter (PF). They are all based on a nonlinear model of the glucose-insulin dynamics in people with type 1 diabetes. Drift is modelled by a Gaussian random walk and is detected based on the statistical tests of the 90-min prediction residuals of the filters. The unscented Kalman filter had the highest average F score of 85.9%, and the smallest average detection delay of 84.1%, with the average detection sensitivity of 82.6%, and average specificity of 91.0%.",

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AB - The purpose of this study is to compare the performance of three nonlinear filters in online drift detection of continuous glucose monitors. The nonlinear filters are the extended Kalman filter (EKF), the unscented Kalman filter (UKF), and the particle filter (PF). They are all based on a nonlinear model of the glucose-insulin dynamics in people with type 1 diabetes. Drift is modelled by a Gaussian random walk and is detected based on the statistical tests of the 90-min prediction residuals of the filters. The unscented Kalman filter had the highest average F score of 85.9%, and the smallest average detection delay of 84.1%, with the average detection sensitivity of 82.6%, and average specificity of 91.0%.

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JF - Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference

ER -

Comparison of three nonlinear filters for fault detection in continuous glucose monitors.

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Keywords

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