Personalized Glycemic Control Program for Patients with Type I Diabetes Mellitus

In this paper, an adaptive fuzzy sliding mode controller is designed to regulate the glucose level in type I diabetes, where its estimation is based on Bergman minimum glucose-insulin Model. All the underlying data in this paper was obtained from the UVA/Padova Type I Diabetes Simulator. The study included a cohort of nine diabetic patient from the simulation platform, comprising three adults, three adolescents, and three children. Firstly, simulation conditions were set, and blood glucose data before meals were obtained from nine patients. Subsequently, parameter identification techniques were employed, utilizing the general parameters of the Bergman Minimal Model as a foundation to derive personalized parameters for each patient's Bergman Minimal Model. Furthermore, in response to the requirements of blood glucose control, we proposed a control strategy combining fuzzy theory and sliding mode control. Considering the individualized parameters among patients, we derived the control strategy of the controller and constructed a SIMULINK simulation system in MATLAB. Through experimentation, we validated the effectiveness of the controller, which effectively controlled blood glucose levels in type I diabetes patients.