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.

通过身体活动控制血糖的一种基于模型的方法。
体育锻炼在减缓2型糖尿病进展中的作用是公认的。然而,除了一般的临床指南外,基于不断变化的个体状况对推荐运动量的定量实时估计在文献中仍然缺失。这项工作的目的是提供一个控制理论公式的运动编码所有运动相关的特征(强度,持续时间,周期)。具体来说,我们根据推荐的身体活动设计了一个反馈律,遵循模型预测控制方法,基于广泛的紧凑型糖尿病进展模型,适当修改以考虑定期运动的长期影响。初步模拟显示了令人鼓舞的结果,与临床证据很好地吻合。这些发现可以作为进一步验证高维糖尿病进展模型控制规律的基础,最终将控制器的预测转化为有意义的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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