Work

Artificial Pancreas under stable MPC: including the Physical Activity effect

Year: 2024

Type: conference-paper

Abstract: : This work presents the application of Model Predictive Control (MPC) for the control of blood glucose concentrationin patients with Type 1 Diabetes Mellitus (T1DM). The main novelty of the algorithm is the inclusion of physical activity effects, i.e. one of the main critical aspects of the disease. The glycemic control is based on a physiological individualized long-term compartmental model. Leveraging on this model, the algorithm is able to control glycemia by performing prediction and estimation of patient’s next states, employing disturbance observers to compensate plant-model mismatches. The overall performance is tested in a cohort of in-silico patients from the FDA-approved UVA/Padova simulator.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.14277264

Authors: Licini, N., Sonzogni, B., Abuin, P., Previdi, F., Gonzalez, A.H., Ferramosca, A

Institutions: University of Bergamo, Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Nacional del Litoral, Instituto de Desarrollo Tecnológico para la Industria Química

Language: English

Topic: Diabetes Management and Research

Subfield: Endocrinology, Diabetes and Metabolism

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W6930820782

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