Restricting Ackerman’s Model Using Pattern Search: A Case Study of Moroccan Type 2 Diabetics

Ackerman model is widely used to describe the glycemic profiles of non-diabetic people. It is an easy-to-use model that gives explicitly the glycemic equation by implementing amplitude and damping parameters. The goal of this paper is to demonstrate that this model is incapable of reproducing the profile glycemic of type 2 diabetic patients. To this end, we consider 50 Morocco type 2 diabetic patients that we equipped with a Continuous Glucose Monitoring (CGM) device. Then, we transform the Ackerman model parameters estimation is transformed into a non-linear optimization problem. To solve this latter, we use pattern search optimization algorithm. The obtained result demonstrates that the Ackerman model is incapable of describing the profile glycemic of diabetic patients. Thus, the necessity of improving this model by doting with sufficient flexibility.