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A nonlinear model predictive controller has been developed to maintain normoglycemia in subjects with type 1 diabetes during fasting conditions such as during overnight fast. The controller employs a compartment model, which represents the glucoregulatory system and includes submodels representing absorption of subcutaneously administered short-acting insulin Lispro and gut absorption. The controller uses Bayesian parameter estimation to determine time-varying model parameters. Moving target trajectory facilitates slow, controlled normalization of elevated glucose levels and faster normalization of low glucose values. The predictive capabilities of the model have been evaluated using data from 15 clinical experiments in subjects with type 1 diabetes. The experiments employed intravenous glucose sampling (every 15 min) and subcutaneous infusion of insulin Lispro by insulin pump (modified also every 15 min). The model gave glucose predictions with a mean square error proportionally related to the prediction horizon with the value of 0.2 mmol L-1 per 15 min. The assessment of clinical utility of model-based glucose predictions using Clarke error grid analysis gave 95% of values in zone A and the remaining 5% of values in zone B for glucose predictions up to 60 min (n = 1674). In conclusion, adaptive nonlinear model predictive control is promising for the control of glucose concentration during fasting conditions in subjects with type 1 diabetes.

Notas/Comentarios de María Elena Hernando:
Algoritmo de control en lazo cerrado para mantener en rangos de normoglucemia la concentración de glucosa en sangre de pacientes con diabetes tipo 1. Es un trabajo pionero en el campo del páncreas artificial, que fue evaluado con pacientes con buenos resultados.

Especificaciones

  • Autor/es: Roman Hovorka, Valentina Canonico, Ludovic J Chassin, Ulrich Haueter, Massimo Massi-Benedetti, Marco Orsini Federici, Thomas R Pieber, Helga C Schaller, Lukas Schaupp, Thomas Vering, Malgorzata E Wilinska.
  • Fecha: 2004-07
  • Publicado en: Physiological Measurement, Volume 25, Number 4, July 2004, Pages 905-920.
  • Idioma: Inglés
  • Formato: PDF
  • Contribución: María Elena Hernando Pérez.
  • Palabras clave: Ingeniería en medicina y biología, Ordenadores y tratamiento de la información, Sistemas de control
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