Since they lack insulin-producing β-cells, patients with type 1 diabetes mellitus (T1DM) need to supply their body with insulin from external sources to manage their blood glucose (BG) concentration and mitigate the long-term effects of chronically increased BG levels. The common way of dosing insulin in T1DM is basal bolus therapy. In this method, patients continuously supply their body with a small amount of insulin that is meant for keeping their BG level more or less constant in case no large disturbances occur. Bolus insulin (which makes up roughly 30–60% of the total insulin amount) on the other hand is used to counterbalance such disturbances. The biggest perturbation of BG is caused by meals that can lead to large postprandial glucose excursions. By far, the most common approach to determine bolus insulin requirements in T1DM is known as Advanced Carbohydrate Counting (ACC). In ACC the bolus insulin amount is determined proportional to the estimated carbohydrate content of the ingested meal. Even though this semi-heuristic approach has proven very valuable in daily practice, its use is not without pitfalls. In this paper we discuss the background, implicit assumptions and limitations of ACC from an engineering perspective and show how concepts from the fields of data-based modeling and control have been successfully used to facilitate the computation of bolus insulin requirements.

由于它们缺乏产生胰岛素的β-细胞，1型糖尿病（T1DM）患者需要从外部来源为体内提供胰岛素，以控制血糖（BG）浓度并减轻BG长期升高的长期影响。在T1DM中给药胰岛素的常见方法是基础推注疗法。通过这种方法，患者可以连续向身体提供少量的胰岛素，这意味着在没有大的干扰发生的情况下，BG的水平或多或少保持恒定。另一方面，大剂量胰岛素（约占胰岛素总量的30–60％）用于抵消此类干扰。BG的最大扰动是由进餐引起的，这些进餐可能导致餐后大量的葡萄糖偏移。到目前为止，确定T1DM中推注胰岛素需求量的最常见方法是高级碳水化合物计数（ACC）。在ACC中，推注胰岛素的量与摄入的膳食中估计的碳水化合物含量成正比。即使这种半启发式方法在日常实践中已被证明非常有价值，但其使用并非没有陷阱。在本文中，我们将从工程角度讨论ACC的背景，隐含假设和局限性，并展示如何成功地使用基于数据的建模和控制领域的概念来促进大剂量胰岛素需求量的计算。