Closed-loop MPC-based artificial pancreas: Handling circadian variability of insulin sensitivity

Pablo Abuin, J. Sereno, A. Ferramosca, A. González
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引用次数: 2

Abstract

Closed-loop glycemic control algorithms have demonstrated the ability to improve glucose regulation in patients with type 1 diabetes mellitus (T1DM), both in silico and clinical research trials. However, many of the proposed control strategies have been developed under time-invariant linear models, without considering the well-know intraday parametric variability. In this work, a recently published pulsatile Zone Model Predictive Control (pZMPC) is analyzed under a real observed pattern of intraday insulin sensitivity (SI), according to the latest updates of the FDA-approved UVA/Padova simulator. To this end, nominal information of the postprandial insulin sensitivity is explicitly included in the control-oriented model to be taken into account in the predictions. The proposed control strategy is evaluated in silico under the FDA-approved UVA/Padova simulator, the performance analysis is done using statistical metrics and it is compared with the invariant version of the aforementioned controller. Results show a significant improvement in the analyzed metrics when the time-variant control-oriented model is considered in the predictions, which justifies the proposed increment in the controller complexity.
基于闭环mpc的人工胰腺:处理胰岛素敏感性的昼夜变化
在计算机和临床研究试验中,闭环血糖控制算法已经证明能够改善1型糖尿病(T1DM)患者的血糖调节。然而,许多提出的控制策略都是在定常线性模型下开发的,而没有考虑众所周知的日内参数变异性。在这项工作中,根据fda批准的UVA/Padova模拟器的最新更新,在真实观察到的日内胰岛素敏感性(SI)模式下分析了最近发表的脉动区模型预测控制(pZMPC)。为此,餐后胰岛素敏感性的名义信息被明确地包含在面向控制的模型中,以便在预测中考虑。在fda批准的UVA/Padova模拟器下对所提出的控制策略进行了计算机评估,使用统计指标进行了性能分析,并将其与上述控制器的不变版本进行了比较。结果表明,当在预测中考虑时变控制导向模型时,所分析的指标有显着改善,这证明了所提出的控制器复杂性增量是正确的。
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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