Design and <i>In Silico</i> Evaluation of an Exercise Decision Support System Using Digital Twin Models.

ABSTRACT:

Background

Managing glucose levels during exercise is challenging for individuals with type 1 diabetes (T1D) since multiple factors including activity type, duration, intensity and other factors must be considered. Current decision support tools lack personalized recommendations and fail to distinguish between aerobic and resistance exercise. We propose an exercise-aware decision support system (exDSS) that uses digital twins to deliver personalized recommendations to help people with T1D maintain safe glucose levels (70-180 mg/dL) and avoid low glucose (<70 mg/dL) during and after exercise.

Methods

We evaluated exDSS using various exercise and meal scenarios recorded from a large, free-living study of aerobic and resistance exercise. The model inputs were heart rate, insuli

SUBMITTER: Young G 

PROVIDER: S-EPMC10973845 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature