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arXiv · 2503.09435

A Model-based Approach for Glucose Control via Physical Activity

Pierluigi Francesco De Paola·Alessandro Borri·Alessia Paglialonga·Pasquale Palumbo·Fabrizio Dabbene
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Abstract

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.

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Pierluigi Francesco De Paola, Alessandro Borri, Alessia Paglialonga, Pasquale Palumbo, Fabrizio Dabbene. 2025-03-12. A Model-based Approach for Glucose Control via Physical Activity. https://arxiv.org/abs/2503.09435

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