Meal Detection in Patients With Type 1 Diabetes: A New Module for the Multivariable Adaptive Artificial Pancreas Control System

@article{Turksoy2016MealDI,
  title={Meal Detection in Patients With Type 1 Diabetes: A New Module for the Multivariable Adaptive Artificial Pancreas Control System},
  author={Kamuran Turksoy and Sediqeh Samadi and Jianyuan Feng and Elizabeth Littlejohn and Lauretta Quinn and Ali Cinar},
  journal={IEEE Journal of Biomedical and Health Informatics},
  year={2016},
  volume={20},
  pages={47-54}
}
A novel meal-detection algorithm is developed based on continuous glucose measurements. Bergman's minimal model is modified and used in an unscented Kalman filter for state estimations. The estimated rate of appearance of glucose is used for meal detection. Data from nine subjects are used to assess the performance of the algorithm. The results indicate that the proposed algorithm works successfully with high accuracy. The average change in glucose levels between the meals and the detection… CONTINUE READING
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