Measures from Nonlinear Dynamics Reflect Glucose Current Sensor Degradation

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.

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