Método para el modelado del nivel de glucemia mediante programación genética

摘要

The invention relates to a method which, by applying evolutionary algorithms to random solutions and data taken from a patient with glycemia, allows the level of glycemia to be modelled in order to obtain a modelling of the level of glucose in future moments when the patient's data is obtained. The data of the patient comprises at least the levels of glucose, intake and rapid-acting and slow-acting insulin over a time interval. The evolutionary algorithm basically consists in applying genetic programming in its variant of evolutionary grammars or grammatical evolution, i.e. applying personalised grammars in a BNF format, personalised mapping processes and concrete error evaluations to the random solutions or to previously generated models in order to obtain an expression that describes and predicts the glucose levels of a patient. The method of the invention is especially suitable for patients suffering from diabetes mellitus.