The role played by physical activity in slowing down the progression of type-2 diabetes is well recognized. However, except for general clinical guidelines, quantitative real-time estimates of the recommended amount of physical activity, based on the evolving individual conditions, are {still missing} in the literature. The aim of this work is to provide a control-theoretical formulation of the exercise encoding all the exercise-related features (intensity, duration, period). Specifically, we design a feedback law in terms of recommended physical activity, following a model predictive control approach, based on a widespread compact diabetes progression model, suitably modified to account for the long-term effects of regular exercise. Preliminary simulations show promising results, well aligned with clinical evidence. These findings can be the basis for further validation of the control law on high-dimensional diabetes progression models to ultimately translate the predictions of the controller into meaningful recommendations.
@article{arxiv.2503.09435,
title = {A Model-based Approach for Glucose Control via Physical Activity},
author = {Pierluigi Francesco De Paola and Alessandro Borri and Alessia Paglialonga and Pasquale Palumbo and Fabrizio Dabbene},
journal= {arXiv preprint arXiv:2503.09435},
year = {2025}
}