Grupo de Control Aplicado (GCA), Instituto LEICI, Facultad de Ingeniería, UNLP-CONICET, 48 y 116 CC, 91 (1900) La Plata, Buenos Aires, Argentina.
Med Biol Eng Comput. 2020 Oct;58(10):2325-2337. doi: 10.1007/s11517-020-02213-w. Epub 2020 Jul 24.
Artificial pancreas (AP) systems have shown to improve glucose regulation in type 1 diabetes (T1D) patients. However, full closed-loop performance remains a challenge particularly in children and adolescents, since these age groups often present the worst glycemic control. In this work, an algorithm based on switched control and time-varying IOB constraints is presented. The proposed control strategy is evaluated in silico using the FDA-approved UVA/ Padova simulator and its performance contrasted with the previously introduced Automatic Regulation of Glucose (ARG) algorithm in the pediatric population. The effect of unannounced meals is also explored. Results indicate that the proposed strategy achieves lower hypo- and hyperglycemia than the ARG for both announced and unannounced meals. Graphical Abstract Block diagram and illustrative example of insulin and glucose evolution over time for the proposed algorithm (ARGAE).
人工胰腺 (AP) 系统已被证明可改善 1 型糖尿病 (T1D) 患者的血糖调节。然而，完全闭环性能仍然是一个挑战，特别是在儿童和青少年中，因为这些年龄组的血糖控制通常最差。在这项工作中，提出了一种基于切换控制和时变 IO 约束的算法。使用 FDA 批准的 UVA/Padova 模拟器对所提出的控制策略进行了计算机仿真，并将其性能与儿科人群中先前介绍的自动葡萄糖调节 (ARG) 算法进行了对比。还探讨了未宣布的膳食的影响。结果表明，与 ARG 相比，所提出的策略在宣布和未宣布的膳食中都能降低低血糖和高血糖的发生。
