Identification of CGM Time Delays and Implications for BG Control in T1DM

  • Florian ReitererEmail author
  • Phillipp Polterauer
  • Guido Freckmann
  • Luigi del Re
Conference paper
Part of the IFMBE Proceedings book series (IFMBE, volume 57)


Continuous glucose monitoring (CGM) systems are becoming increasingly popular for the management of type 1 diabetes mellitus (T1DM). However, one of the limitations of using CGM information for blood glucose (BG) control is the fact that the CGM sensor measures the glucose not in the blood, but in the interstitial fluid. The current paper shows how a sensor and patient-specific time delay between interstitial glucose (IG) and blood glucose (BG) can be identified from CGM recordings and BG measurements. The resulting time delay values were found to be highly patient-specific and correlated with patient characteristics. Furthermore, it was found that the CGM time delays are a good predictor for the required total daily dose (TDD) of insulin, as well as for the carbohydrate-to-insulin-ratio (CIR). Based on these findings we introduce a method of how insulin therapy in T1DM could possibly be adjusted based on identified CGM time delays.


Continuous Glucose Monitoring Time delays Blood glucose control Type 1 diabetes System identification 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Cengiz E, Tamborlane W V. A Tale of Two Compartments: Interstitial Versus Blood Glucose Monitoring Diabetes Technol Ther. 2009;11:S11-S16Google Scholar
  2. 2.
    Basu A, Dube S, Slama M, et al. Time Lag of Glucose From Intravascular to Interstitial Compartment in Humans Diabetes. 2013;62:4083-4087Google Scholar
  3. 3.
    Schmelzeisen-Redeker G, Staib A, Strasser M, Müller U, Schoemaker M. Overview of a Novel Sensor for Continuous Glucose Monitoring J Diabetes Sci Technol. 2013;7:808-814Google Scholar
  4. 4.
    Rebrin K, Sheppard N F Jr, Steil G M. Use of Subcutaneous Interstitial Fluid Glucose to Estimate Blood Glucose: Revisiting Delay and Sensor Offset J Diabetes Sci Technol. 2010;4:1087-1098Google Scholar
  5. 5.
    Keenan D B, Mastrototaro J J, Voskanyan G, Steil G M. Delays in Minimally Invasive Continuous Glucose Monitoring Devices: A Review of Current Technology J Diabetes Sci Technol. 2009;3:1207-1214Google Scholar
  6. 6.
    Schmelzeisen-Redeker G, Schoemaker M, Kirchsteiger H, Freckmann G, Heinemann L, Del Re L. Time Delay of CGM Sensors: Relevance, Causes, and Countermeasures J Diabetes Sci Technol. 2015;9:1006-1015Google Scholar
  7. 7.
    Del Favero S, Facchinetti A, Sparacino G, Cobelli C. Improving Accuracy and Precision of Glucose Sensor Profiles: Retrospective Fitting by Constrained Deconvolution IEEE Trans Biomed Eng. 2014;61:1044-1053Google Scholar
  8. 8.
    Vettoretti M, Facchinetti A, Del Favero S, Sparacino G, Cobelli C. On-line calibration of glucose sensors from the measured current by a time-varying calibration function and Bayesian priors IEEE Trans Biomed Eng. 2015;PP:1-1Google Scholar
  9. 9.
    Steil G M, Rebrin K, Hariri F, et al. Interstitial fluid glucose dynamics during insulin-induced hypoglycaemia Diabetologia. 2005;48:1833-1840Google Scholar
  10. 10.
    Patek S D, Lv D, Ortiz E A, et al. Prediction Methods for Blood Glucose Concentration: Design, Use and Evaluationch. Empirical Representation of Blood Glucose Variability in a Compartmental Model. Springer International Publishing Switzerland 2016Google Scholar
  11. 11.
    Kirchsteiger H, Efendic H, Freckmann G, Del Re L. LMI-based online estimation of a time-varying time-delay in continuous glucose measurement devices in CDC 2014, Proc IEEE Conf Decis Control:6981-6986 2014Google Scholar
  12. 12.
    Freckmann G, Pleus S, Link M, Zschornack E, Klötzer H-M, Haug C. PerformanceEvaluation of Three Continuous Glucose Monitoring Systems: Comparison of SixSensors per Subject in Parallel J Diabetes Sci Technol. 2013;7:842-853Google Scholar
  13. 13.
    Facchinetti A, Sparacino G, Cobelli C. Reconstruction of Glucose in Plasma from Interstitial Fluid Continuous Glucose Monitoring Data: Role of Sensor Calibration J Diabetes Sci Technol. 2007;1:617-623Google Scholar
  14. 14.
    Wei C, Lunn D J, Acerini C L, et al. Measurement delay associated with the Guardian\(\textregistered \) RT continuous glucose monitoring system Diabetic Med. 2010;27:117-122Google Scholar
  15. 15.
    Facchinetti A, Del Favero S, Sparacino G, Castle J R, Ward W K, Cobelli C. Modeling the Glucose Sensor Error IEEE Trans Biomed Eng. 2014;61:620-629Google Scholar
  16. 16.
    Walsh J, Roberts R, Bailey T. Guidelines for Insuin Dosing in Continuous Subcutaneous Insulin Infusion Using New Formulas from a Retrospective Study of Individuals with Optimal Glucose Levels J Diabetes Sci Technol. 2010;4:1174-1181Google Scholar
  17. 17.
    King A B, Armstrong D U. A Prospective Evaluation of Insulin Dosing Recommendations in Patients with Type 1 Diabetes at Near Normal Glucose Control: Bolus Dosing J Diabetes Sci Technol. 2007;1:42-46Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Florian Reiterer
    • 1
    Email author
  • Phillipp Polterauer
    • 1
  • Guido Freckmann
    • 2
  • Luigi del Re
    • 1
  1. 1.Institute for Design and Control of Mechatronical SystemsDESREG, Johannes Kepler University LinzLinzAustria
  2. 2.Institut Für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbHUniversity of UlmUlmGermany

Personalised recommendations