Blood Glucose Management Using the Improved Hovorka's Model: A Case Study of an Adolescent Diabetes Patient's Meal Disturbance Scenario

The meal is one of the elements that affect blood glucose levels. Given that diabetes is a metabolic disease in which insulin production and utilization are impaired, resulting in elevated blood glucose levels (BGL) because of the devastation caused by the [β-cell that regulates BGL, it is critical to have a better control architecture to combat this challenge. This research work is aimed at tracking and regulating an adolescent's meal protocol for a day. The enhanced Hovoka's model was used as the diabetes model in this study, and the controller's input is an iterative tree structure that employs two Mamdani fuzzy inference systems to provide a stabilizing control protocol for the patient's insulin administration. For evaluation and validation, the internationally acceptable glycemic control parameters and the control variability grid analysis were utilized, demonstrating that the control system operated satisfactorily.