Key result
Programmed physical activity management using a pulsatile Zone Model Predictive Control algorithm achieved a median time in range (70-180 mg/dL) of 96.6% compared to 94.7% for non-programmed management in virtual patients with Type 1 diabetes.
Why the study?
Does a pulsatile Zone Model Predictive Control (pZMPC) algorithm improve blood glucose concentration control in in-silico patients with Type 1 Diabetes Mellitus?
Does a pulsatile Zone Model Predictive Control (pZMPC) algorithm improve blood glucose concentration control in in-silico patients with Type 1 Diabetes Mellitus?
A pulsatile Zone Model Predictive Control algorithm incorporating physical activity effects was developed and evaluated for blood glucose control in an in-silico model of Type 1 Diabetes.
pZMPC with physical activity modeling may reduce hypoglycemia in T1DM simulations; leaves open prospective human validation before clinical consideration.
This study presents the application of a pulsatile Zone Model Predictive Control (pZMPC) aimed at controlling blood glucose concentration in individuals affected by Type 1 Diabetes Mellitus (T1DM), considering physical activity effects, i.e. one of the main critical aspects of the disease. The glycemic control relies on a physiological individualized long-term model. Leveraging this model, the algorithm performs prediction and estimation of the patient’s future states, employing a disturbance observer to compensate for plant-model mismatches. The efficacy of this approach is evaluated in a cohort of in-silico patients from the FDA-approved UVA/Padova simulator.
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Licini et al. (2024) studied Type 1 Diabetes Mellitus (n=10). Pulsatile Zone Model Predictive Control (pZMPC) with programmed physical activity vs. pZMPC with non-programmed physical activity was evaluated on Percentage of time spent within the euglycemic range 70-180 mg/dL (T70-180) under perfectly announced disturbances. Programmed physical activity management using a pulsatile Zone Model Predictive Control algorithm achieved a median time in range (70-180 mg/dL) of 96.6% compared to 94.7% for non-programmed management in virtual patients with Type 1 diabetes.
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