论文标题
一种在线随机优化方法，用于2型糖尿病中的胰岛素强化，并注意伪血糖症
An Online Stochastic Optimization Approach for Insulin Intensification in Type 2 Diabetes with Attention to Pseudo-Hypoglycemia
论文作者
论文摘要
在本文中，我们提出了一种无模型的方法，用于计算2型糖尿病（T2D）受试者的长效胰岛素剂量，以使其血糖（BG）浓度在安全范围内。提出的策略通过为定义的成本函数使用零订单在线随机优化方法来调整所提出的控制定律的参数。该策略使用基于自适应力矩估计的方法在名为Anabelief的方法中使用递归最小二平方（RLS）方案获得的梯度估计。此外，我们还展示了通过反馈评分测量的提议策略如何适应一种称为相对低血糖或伪糖血糖（PHG）的现象，在该现象中，受试者经历低血糖症症状，根据其BG浓度的速度降低了低血糖症状。证明了胰岛素计算策略的性能，并使用具有三种不同模型的模拟与当前的胰岛素计算策略进行了比较。
In this paper, we present a model free approach to calculate long-acting insulin doses for Type 2 Diabetic (T2D) subjects in order to bring their blood glucose (BG) concentration to be within a safe range. The proposed strategy tunes the parameters of a proposed control law by using a zeroth-order online stochastic optimization approach for a defined cost function. The strategy uses gradient estimates obtained by a Recursive Least Square (RLS) scheme in an adaptive moment estimation based approach named AdaBelief. Additionally, we show how the proposed strategy with a feedback rating measurement can accommodate for a phenomena known as relative hypoglycemia or pseudo-hypoglycemia (PHG) in which subjects experience hypoglycemia symptoms depending on how quick their BG concentration is lowered. The performance of the insulin calculation strategy is demonstrated and compared with current insulin calculation strategies using simulations with three different models.
