The ARG algorithm was successfully validated in a pilot clinical trial, encouraging further tests with a larger number of patients and in outpatient settings.
In this work, a low-order model designed for glucose regulation in Type 1 Diabetes Mellitus (T1DM) is obtained from the UVA/Padova metabolic simulator. It captures not only the nonlinear behavior of the glucose-insulin system, but also intrapatient variations related to daily insulin sensitivity (SI) changes. To overcome the large inter-subject variability, the model can also be personalized based on a priori patient information. The structure is amenable for linear parameter varying (LPV) controller design, and represents the dynamics from the subcutaneous insulin input to the subcutaneous glucose output. The efficacy of this model is evaluated in comparison with a previous control-oriented model which in turn is an improvement of previous models. Both models are compared in terms of their open-and closed-loop differences with respect to the UVA/Padova model. The proposed model outperforms previous T1DM controloriented models, which could potentially lead to more robust and reliable controllers for glycemia regulation.
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