Evolutionary LTI models of Glucose-Carbohidrate-Insulin interaction


A key issue for a proper control and treatment of diabetes patients is to have an accurate model of the interaction between glucose, carbohidrates (CHO) and exogenous insulin infusions. There are two main modeling trends. The rst trend is focused on the physiology and pharmacokinetics of the glucoregulatory system in order to provide realistic in-silico patients for developing further medical studies. The second trend is focused on models that are to be employed in the so called articial pancreas (AP). Currently comercialized APs implement predictive stategies based on a linear and time-invariant (LTI) models described by a single-input single-output (SISO) transfer function; which is usually identied using in-silico patients. The most recent approach to personalized models consists of testing the actual patient with CHO intakes and insulin bolus for registering the body response in terms of glucose and insulin rate appearence in blood. Considering these responses as inputs instead of intakes and insulin infusions recorded in a log simplies the model considerably; but it requires to visit the hospital and to follow the test protocol.

J. Manuel Colmenar
J. Manuel Colmenar
Artificial Intelligence Professor

Mis intereses de investigación se centran en las metaheurísticas aplicadas a problemas de optimización. He trabajado en diferentes problemas de optimización combinatoria aplicando algoritmos trajectoriales como GRASP o VNS. Además, estoy muy interesado en las aplicaciones de la Evolución Gramatical, específicamente en el dominio de los modelos y la predicción, como alternativa a los enfoques de aprendizaje automático.