PEDIATRIC GLUCOSE REGULATION WITHOUT PRE-MEAL INSULIN BOLUSES: AN APPROACH BASED ON SWITCHED CONTROL AND TIME-VARYING IOB CONSTRAINTS

Session Name
CLOSED-LOOP SYSTEM AND ALGORITHM
Session Type
E-POSTER VIEWING (EXHIBITION HOURS)
Date
20.02.2020, Thursday
Session Time
09:30 - 15:30
Channel
E-Poster Area
Lecture Time
09:38 - 09:39
Presenter
  • Fabricio Garelli, Argentina
Authors
  • Emilia Fushimi, Argentina
  • Cecilia Serafini, Argentina
  • Hernan De battista, Argentina
  • Ricardo Sanchez peña, Argentina
  • Fabricio Garelli, Argentina

Abstract

Background and Aims

AP systems have shown to improve glucose regulation in T1D patients. However, full closed-loop performance remains a challenge particularly in children and adolescents, since these age groups often present the worst glycemic control.

Methods

In this work, a new algorithm based on switched control and time-varying IOB constraints is presented (ARGAE). This method is a combination of ideas from the previously introduced Automatic Regulation of Glucose (ARG) algorithm, which features no pre-meal insulin boluses [1], and the Amplitude Enable (AE) mode, which allows the controller to act more aggressively at the beginning of meal intake without risking postprandial hypoglycemia [2]. The proposed control strategy is evaluated in silico and its performance contrasted with the ARG algorithm in the pediatric population.

Results

The in silico tests performed indicate that the use of the Amplitude Enable layer can help increase the time in euglycemia for both adolescent and children age groups (see tables 1 and 2). Hypoglycemia is significantly reduced in children and completely avoided in adolescents. This is an important upside of the ARGAE since a severe hypoglycemia episode is one of the most dangerous situations for people with T1D.

fig (tables).jpg

Conclusions

Simulations show that the proposed algorithm improves the performance of the ARG algorithm.

[1] P. Colmegna, F. Garelli, H. D. Battista and R. Sánchez-Peña, Control Engineering Practice, no. 74, pp. 22-32, 2018.

[2] E. Fushimi, N. Rosales, H. De Battista and F. Garelli, Biomed Signal Process Control, vol. 45, pp. 1-9, 2018.

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