Capturing children food exposure using wearable cameras and deep learning.

ABSTRACT: Children's dietary habits are influenced by complex factors within their home, school and neighborhood environments. Identifying such influencers and assessing their effects is traditionally based on self-reported data which can be prone to recall bias. We developed a culturally acceptable machine-learning-based data-collection system to objectively capture school-children's exposure to food (including food items, food advertisements, and food outlets) in two urban Arab centers: Greater Beirut, in Lebanon, and Greater Tunis, in Tunisia. Our machine-learning-based system consists of 1) a wearable camera that captures continuous footage of children's environment during a typical school day, 2) a machine learning model that automatically identifies images related to food from the collected da

SUBMITTER: Elbassuoni S 

PROVIDER: S-EPMC10042366 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature