Closed-loop glycemic control algorithms have demonstrated the ability to improve glucose regulation in patients with type 1 diabetes mellitus (T1D), both in silico and clinical trials. Many of the proposed control strategies have been developed, based on time-invariant linear models, without considering the parametric variations of T1DM subjects. In this work, a pulsatile Zone Model Predictive Control (pZMPC) is proposed, which explicitly considers patterns of intra-day insulin sensitivity (SI), according to the latest updates of the FDA-approved UVA/Padova simulator. Results show a significant improvement in the performance, which a-priori justifies the increment in the controller complexity.

(2022). Artificial pancreas under periodic MPC for trajectory tracking: handling circadian variability of insulin sensitivity . Retrieved from http://hdl.handle.net/10446/228585

Artificial pancreas under periodic MPC for trajectory tracking: handling circadian variability of insulin sensitivity

Ferramosca, Antonio;
2022-09

Abstract

Closed-loop glycemic control algorithms have demonstrated the ability to improve glucose regulation in patients with type 1 diabetes mellitus (T1D), both in silico and clinical trials. Many of the proposed control strategies have been developed, based on time-invariant linear models, without considering the parametric variations of T1DM subjects. In this work, a pulsatile Zone Model Predictive Control (pZMPC) is proposed, which explicitly considers patterns of intra-day insulin sensitivity (SI), according to the latest updates of the FDA-approved UVA/Padova simulator. Results show a significant improvement in the performance, which a-priori justifies the increment in the controller complexity.
Abuin, Pablo; Ferramosca, Antonio; Toffanin, Chiara; Magni, Lalo; Gonzalez, Alejandro H.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10446/228585
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