Personalized Adaptive CBR Bolus Recommender System for Type 1 Diabetes

Type 1 diabetes mellitus (T1DM) is a chronic disease. Those who have it must administer themselves with insulin to control their blood glucose level. It is difficult to estimate the correct insulin dosage due to the complex glucose metabolism, which can lead to less than optimal blood glucose levels. This paper presents PepperRec, a case-based reasoning (CBR) bolus insulin recommender system capable of dealing with an unrestricted number of situations in which T1DM persons can find themselves. PepperRec considers several factors that affect glucose metabolism, such as data about the physical activity of the user, and can also cope with missing values for these factors. Based on CBR methodology, PepperRec uses new methods to adapt past recommendations to the current state of the user, and retains updated historical patient information to deal with slow and gradual changes in the patient over time (concept drift). The proposed approach is tested using the UVA/PADOVA simulator with 33 virtual subjects and compared with other methods in the literature, and with the default insulin therapy of the simulator. The achieved results demonstrate that PepperRec increases the amount of time the users are in their target glycaemic range, reduces the time spent below it, while maintaining, or even reducing, the time spent above it.

I. Introduction

Type 1 Diabetes Mellitus (T1DM) is a chronic metabolic disease characterised by the autoimmune destruction of the beta cells of the endocrine pancreas responsible for controlling Blood Glucose (BG) levels through the secretion of insulin. There are no actual global statistics regarding the number of people suffering from T1DM [1], but the American Diabetes Association estimates that there are approximately 1.25 million American adults and children with T1DM. According to the International Diabetes Federation, the highest incidence rates are in Europe, where there are approximately 140,000 children with T1DM and 21,600 new cases every year [2].