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Measures from Nonlinear Dynamics Reflect Glucose Current Sensor Degradation

  • Eric MauritzenEmail author
  • Arnold Mandell
  • David Tallman
  • Bruce Buckingham
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 6)

Abstract

Advancements in continuous glucose monitoring technology has enabled development of closed-loop insulin-glucagon delivery systems. Monitoring the reliability and fidelity of glucose current, \(\varSigma I_g(t)\), becomes essential for the safety of patients utilizing these closed loop systems (Barnaba et al., Diab Technol Ther 5:27–31, 2005) [2]. Because time series of \(\varSigma I_g(t)\) evidence chaotic nonlinear hyperbolic (expanding and mixing) dynamical behavior (Ruelle and Takens, Commun Math Phys 20(3):167–192, 1971) [10], we use the complexity measures from dynamical measure theory to discriminate normal function from progressive dysfunction in glucose sensors (Cornfeld et al., Ergodic Theory, 2012) [3]. We present a method of characterizing the \(\varSigma I_g(t)\) from the continuous glucose monitor signal, CGM, using a set of entropy equivalent information measures (EEIM) that, when combined with the use of a support vector machine, were found to distinguish between functional and failing continuous glucose sensors.

Keywords

Support Vector Machine Continuous Glucose Monitoring Hurst Exponent Commun Math Phys Continuous Glucose Monitor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This work was funded by the Juvenile Diabetes Research Foundation and John Fetzer Memorial Trust.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Eric Mauritzen
    • 1
    Email author
  • Arnold Mandell
    • 1
  • David Tallman
    • 1
  • Bruce Buckingham
    • 2
  1. 1.University of California San DiegoSan DiegoUSA
  2. 2.Department of Pediatric EndocrinologyStanford UniversityStanfordUSA

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