Predicting blood glucose levels for a type I diabetes patient by combination of autoregressive with one compartment open model

Abstract

Preventing complications in diabetes as well as support physicians and patients to treat the disease optimally, prediction of blood glucose levels is essential. In the most common treatment of type I diabetes, the diabetic measures the blood glucose level daily, based on which a proper dosage can be determined. Additionally, there are several other factors that affect the blood glucose concentration, such as carbohydrate intake and level of exercise. One of the main challenges is to make accurate long term predictions. Autoregressive models in combination with compartment models for estimating the insulin concentration can be determined as the first approach to this purpose. This paper provides a snapshot of the state-of-the-art for the model predictor, testing the results and comparing them with results from short-term prediction.