Data-driven meal events detection using blood glucose response patterns.

ABSTRACT:

Background

In the Diabetes domain, events such as meals and exercises play an important role in the disease management. For that, many studies focus on automatic meal detection, specially as part of the so-called artificial [Formula: see text]-cell systems. Meals are associated to blood glucose (BG) variations, however such variations are not peculiar to meals, it mostly comes as a combination of external factors. Thus, general approaches such as the ones focused on glucose signal rate of change are not enough to detect personalized influence of such factors. By using a data-driven individualized approach for meal detection, our method is able to fit real data, detecting personalized meal responses even when such external factors are implicitly present.

Methods

The method is

SUBMITTER: F de Carvalho D 

PROVIDER: S-EPMC10709931 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature