Real-time insulin bolusing for unannounced meals with artificial pancreas. (February 2017)

• Record Type: Journal Article
• Authors: Turksoy, Kamuran; Hajizadeh, Iman; Samadi, Sediqeh; Feng, Jianyuan; Sevil, Mert; Park, Minsun; Quinn, Laurie; Littlejohn, Elizabeth; Cinar, Ali
• Is Part Of: Control engineering practice. Volume 59(2017)
• Page Start: 159
• Page End: 164
• Publication Date: 2017-02
• Subjects: Type 1 diabetes -- Artificial pancreas -- Unannounced meals -- Bolus calculation -- Hyperglycemia; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2016.08.001
• Languages: English
• ISSNs: 0967-0661

Abstract

Abstract: Post-prandial hyperglycemia can occur more frequently in artificial pancreas systems without meal announcements that trigger insulin boluses. Meal announcements are manual feedforward inputs. We have developed a meal-detection and meal bolusing algorithm based on continuous glucose measurements without manual information from patients. 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 and calculation of meal boluses. The algorithm is tested in simulation and clinical environments. The proposed algorithm decreases the frequency, duration and magnitude of hyperglycemia without causing any additional hypoglycemia. Abstract : Graphical abstract: Abstract : Highlights A novel meal detection and meal bolusing algorithm is developed. The developed system uses only continuous glucose monitoring measurements in real time. The algorithm is tested in both simulation and clinical environments. Hyperglycemia is decreased significantly. A new module for the integrated multivariable adaptive artificial pancreas.