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Adaptive multivariable closed-loop control of blood glucose concentration in patients with Type 1 Diabetes

机译:1型糖尿病患者血糖浓度的自适应多变量闭环控制

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Closed-loop control of blood glucose concentration is an alternative treatment for Diabetes patients by automatically controlling their blood glucose level. Recursive time-series models are found to be powerful tool for prediction and control of glucose concentration. However, the stability of such models cannot be guaranteed by regular identification methods. In this paper, we use a constrained optimization method for stability of models. Generalized predictive controller (GPC) is used to close the loop. Physiological signals are used and a multivariable model is created that also includes insulin on-board information to prevent hypoglycemia events. Seven experiments with 3 different patients are done. Results show GPC with constrained identification method and physiological signals can regulate blood glucose concentration successfully.
机译:通过自动控制血糖水平,对血糖浓度进行闭环控制是糖尿病患者的另一种治疗方法。递归时间序列模型被发现是预测和控制葡萄糖浓度的有力工具。但是,此类模型的稳定性无法通过常规识别方法来保证。在本文中,我们使用约束优化方法来保证模型的稳定性。通用预测控制器(GPC)用于闭环。使用生理信号,并创建一个多变量模型,该模型还包含胰岛素内置信息以防止发生低血糖事件。对3位不同的患者进行了7次实验。结果表明,GPC具有受限的识别方法,并且生理信号可以成功地调节血糖浓度。

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