The application of Model Predictive Control to normalize glycemia of critically ill patients

T. Van Herpe, Niels Haverbeke, B. Pluymers, G. Van den Berghe, B. De Moor
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引用次数: 15

Abstract

In this paper we propose a Model based Predictive Controller (MPC) to be used for glycemia control in critically ill patients. A model, that is particularly developed for describing the glucose and the insulin dynamics of these patients, is estimated for each individual patient and re-estimated as new measurements are obtained. Both a quantitative and a qualitative analysis are performed with respect to a real-life dataset from 19 critically ill patients. In the first analysis the robustness of the MPC is tested assuming a once per hour or a once per four hours insulin adaptation frequency is imposed. The second analysis is characterized by a comparison between the MPC insulin infusion sequence and the insulin flows (determined by the nurse) that were effectively administered to the patient. The contribution of this paper is the development of an MPC for glycemia control in the Intensive Care Unit (ICU). The penalty index, which is a specific concept for quantitative analysis of glycemia control in the ICU, is also proposed. The results of the developed MPC are satisfactory both in terms of control behavior (reference tracking and the suppression of unknown disturbance factors) and clinical acceptability.
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模型预测控制在危重患者血糖正常化中的应用
本文提出了一种基于模型的预测控制器(MPC),用于危重患者的血糖控制。一个专门用来描述这些患者的葡萄糖和胰岛素动态的模型,对每个患者进行估计,并在获得新的测量结果时重新估计。对来自19名危重患者的真实数据集进行了定量和定性分析。在第一个分析中,假设施加每小时一次或每四小时一次的胰岛素适应频率,对MPC的稳健性进行了测试。第二个分析的特点是MPC胰岛素输注顺序和胰岛素流量(由护士确定)之间的比较,有效地给病人。本文的贡献是在重症监护病房(ICU)的血糖控制MPC的发展。并提出了惩罚指数这一定量分析ICU血糖控制的具体概念。开发的MPC在控制行为(参考文献跟踪和抑制未知干扰因素)和临床可接受性方面的结果都令人满意。
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