Analysis of commonly used meal models for type 1 diabetes from an identification perspective

The development of new automatic insulin delivery strategies is based on the use of simulators of virtual patients with type 1 diabetes. These simulators are often limited due to a lack of description of realistic scenarios and disturbances. One of the main disturbances ever present in the patients’ lives is meals, but the glucose response to meals has great variability among meal compositions and patients. Most widely used meal models in simulators have a single carbohydrate input, limiting the description of the meal compositions. This paper aims to analyze the performance of the most widely used meal models for type 1 diabetes in different meal composition scenarios while exploring the feasibility of a systematic identification procedure.