Closed-loop glycemic control algorithms have demonstrated the ability to improve glucose regulation in patients with type 1 diabetes mellitus (T1DM), both in silico and clinical research trials. However, many of the proposed control strategies have been developed under time-invariant linear models, without considering the well-know intraday parametric variability. In this work, a recently published pulsatile Zone Model Predictive Control (pZMPC) is analyzed under a real observed pattern of intraday insulin sensitivity (SI ), according to the latest updates of the FDA-approved UVA/Padova simulator. To this end, nominal information of the postprandial insulin sensitivity is explicitly included in the control-oriented model to be taken into account in the predictions. The proposed control strategy is evaluated in silico under the FDA-approved UVA/Padova simulator, the performance analysis is done using statistical metrics and it is compared with the invariant version of the aforementioned controller. Results show a significant improvement in the analyzed metrics when the time-variant control-oriented model is considered in the predictions, which justifies the proposed increment in the controller complexity.

(2020). Closed-loop MPC-based artificial pancreas: Handling circadian variability of insulin sensitivity . Retrieved from http://hdl.handle.net/10446/171210

Closed-loop MPC-based artificial pancreas: Handling circadian variability of insulin sensitivity

Ferramosca, Antonio;
2020-01-01

Abstract

Closed-loop glycemic control algorithms have demonstrated the ability to improve glucose regulation in patients with type 1 diabetes mellitus (T1DM), both in silico and clinical research trials. However, many of the proposed control strategies have been developed under time-invariant linear models, without considering the well-know intraday parametric variability. In this work, a recently published pulsatile Zone Model Predictive Control (pZMPC) is analyzed under a real observed pattern of intraday insulin sensitivity (SI ), according to the latest updates of the FDA-approved UVA/Padova simulator. To this end, nominal information of the postprandial insulin sensitivity is explicitly included in the control-oriented model to be taken into account in the predictions. The proposed control strategy is evaluated in silico under the FDA-approved UVA/Padova simulator, the performance analysis is done using statistical metrics and it is compared with the invariant version of the aforementioned controller. Results show a significant improvement in the analyzed metrics when the time-variant control-oriented model is considered in the predictions, which justifies the proposed increment in the controller complexity.
Abuin, Pablo; Sereno, Juan E.; Ferramosca, Antonio; Gonzalez, Alejandro H.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/171210
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