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Measures from Nonlinear Dynamics Reflect Glucose Current Sensor Degradation

'International Conference on Applications in Nonlinear Dynamics'
Mauritzen, E.Mandell, A.Tallman, D.Buckingham, B. University of California,
San Diego, USA

Department of Pediatric Endocrinology,
Stanford University,
2016 Physics

Advancements in continuous glucose monitoring technology has enabled development of closed-loop insulin-glucagon delivery systems. Monitoring the reliability and fidelity of glucose current, () Σ 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).

Because time series of () Σ 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).

We present a method of characterizing the () Σ 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.

The article was published in: Proceedings of: 'International Conference on Applications in Nonlinear Dynamics', Springer: 189-193.

Full article

This work was supported (in part) by the Fetzer Franklin Fund of the John E. Fetzer Memorial Trust.