Enhancing glucose sensor models: modeling the drop-outs

Diabetes Technology & Therapeutics
Ali EmamiAhmad Haidar

Abstract

Computer simulation environments have been used in the development of many artificial pancreas systems. A glucose sensor model is an essential part of these environments, and different models have been proposed. However, not one of these models accounts for drop-outs of sensor readings, a well-known phenomenon caused by physical pressure on the sensor site. In this work, we have proposed an enhanced model that accounts for drop-outs and demonstrated its improvement over the existing one-compartment model. Potential drop-outs were augmented to the existing model, and their incidences and magnitudes were estimated simultaneously with the model parameters using the Bayesian approach. Drop-outs and model parameters were estimated from data collected from 15 subjects with type 1 diabetes who underwent an artificial pancreas study. Model fitting and parameter estimates were contrasted between the enhanced model and the existing one-compartment model. Both models achieved similar parameter estimates (P=not significant) and were all physiologically plausible. The enhanced model further estimated 1.71 drop-outs per day, which improved model fit (weighted residual reduced from [minimum -4%, maximum 3%] to [-3%, 2%]) and reduced significa...Continue Reading

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Citations

Feb 18, 2016·Diabetes Technology & Therapeutics·Andrea FacchinettiClaudio Cobelli
May 26, 2017·Diabetes Technology & Therapeutics·Udo Hoss, Erwin Satrya Budiman
Oct 6, 2016·Diabetologia·Craig A BeamUNKNOWN Type 1 Diabetes TrialNet Study Group

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