Parameter estimation of a meal glucose-insulin model for TIDM patients from therapy historical data.

摘要: The effect of meal on blood glucose concentration is a key issue in diabetes mellitus because its estimation could be very useful therapy decisions. In the case type 1 (T1DM), based automatic insulin delivery requires closed-loop control system to maintain euglycaemia even postprandial state. Thus, mathematical modelling metabolism relevant predict metabolic state patient. Moreover, eating habits are characteristic each person, so it interest that models intake allow personalise glycaemic patient using historical data, is, daily measurements and records carbohydrate supply. here, model includes effects analysed order establish criteria for data-based personalisation. analysis sensitivity identifiability parameters, parameter problem was resolved via two algorithms: particle swarm optimisation evonorm. results show can tool estimate status according her/his data.