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Prediction Methods for Blood Glucose Concentration pp 107–132Cite as

Predicting Glycemia in Type 1 Diabetes Mellitus with Subspace-Based Linear Multistep Predictors

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Abstract

A major challenge for a person with diabetes is to adapt insulin dosage regimens and food intake to keep blood glucose within tolerable limits during daily life activities. The accurate prediction of blood glucose levels in response to inputs would support the patients with invaluable information for appropriate on-the-spot decision making concerning the management of the disease. Against this background, in this paper we propose multistep data-driven predictors to the purpose of predicting blood glucose multiple steps ahead in the future. We formulate the predictors based on the state-space construction step in subspace identification methods for linear systems. The clinical data of 14 type 1 diabetic patients collected during a 3-days long hospital visit were used. We exploited physiological models from the literature to filter the raw information on carbohydrate and insulin intakes in order to retrieve the inputs signals to the predictors. Predictions were based on the collected CGMS measurements, recalibrated against finger stick samples and smoothed through a regularization step. Performances were assessed with respect to YSI blood glucose samples and compared to those achieved with a Kalman filter identified from data. Results proved the competitiveness of the proposed approach.

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Acknowledgments

This research was partly supported by the European project DIAdvisor \(^{\text {TM}}\), FP7 IST-216592 and the Swedish Research Council by the LCCC Linnaeus Center and the ELLIIT Excellence Center.

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Authors and Affiliations

  1. Department of Automatic Control, Lund University, PO Box 118, 221 00, Lund, Sweden

    Marzia Cescon & Rolf Johansson

  2. Department of Endocrinology, Montpellier University Hospital, University of Montpellier, Montpellier, France

    Eric Renard

Authors
  1. Marzia Cescon
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  2. Rolf Johansson
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  3. Eric Renard
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Corresponding author

Correspondence to Rolf Johansson .

Editor information

Editors and Affiliations

  1. Institute for Design and Control of Mechatronical Systems, Johannes Kepler University Linz, Linz, Austria

    Harald Kirchsteiger

  2. Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark

    John Bagterp Jørgensen

  3. Institut de Génomique Fonctionnelle de Montpellier, Montpellier cedex 5, France

    Eric Renard

  4. Institute for Design and Control of Mechatronical Systems, Johannes Kepler University Linz, Linz, Austria

    Luigi del Re

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Cescon, M., Johansson, R., Renard, E. (2016). Predicting Glycemia in Type 1 Diabetes Mellitus with Subspace-Based Linear Multistep Predictors. In: Kirchsteiger, H., Jørgensen, J., Renard, E., del Re, L. (eds) Prediction Methods for Blood Glucose Concentration. Lecture Notes in Bioengineering. Springer, Cham. https://doi.org/10.1007/978-3-319-25913-0_7

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  • DOI: https://doi.org/10.1007/978-3-319-25913-0_7

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  • Print ISBN: 978-3-319-25911-6

  • Online ISBN: 978-3-319-25913-0

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