Modeling Physical Activity Impact on Glucose Dynamics in People with Type 1 Diabetes for a Fully Automated Artificial Pancreas

TL;DR

This paper develops and validates a physiological and control-oriented model of blood glucose response to moderate aerobic activity in Type 1 diabetes patients, aiming to improve automated insulin delivery systems.

Contribution

It introduces a combined physiological and transfer function model capturing exercise effects on glucose dynamics for automated diabetes management.

Findings

Model accurately predicts glucose response during physical activity.

Enhanced insulin utilization phases improve model fidelity.

Results support development of fully automated closed-loop systems.

Abstract

In this paper, models of the blood glucose (BG) dynamics in people with Type 1 diabetes (T1D) in response to moderate intensity aerobic activity are derived from physiology-based first principles and system identification experiments. We show that by enhancing insulin-dependent glucose utilization by the tissues in two phases, a rapid short-term increase in insulin-independent glucose clearance and augmented glucose uptake, and a long-term sustained increase sensitivity to insulin action, a metabolic model able to reproduce the effects of activity on glucose disposal is obtained. Second, a control-oriented transfer function model is proposed to predict the BG response to an exercise bout modeled as a step change in heart rate (HR). Results comparing model predictions with actual patients data collected in a series of experimental sessions including physical activity (PA) are presented. The findings will contribute to the design of a fully automated closed-loop for improved glucose control in conditions of daily life for people with T1D.