Controlled and Real-Life Investigation of Optical Tracking Sensors in Smart Glasses for Monitoring Eating Behavior Using Deep Learning: Cross-Sectional Study.

Journal: JMIR mHealth and uHealth
PMID:

Abstract

BACKGROUND: The increasing prevalence of obesity necessitates innovative approaches to better understand this health crisis, particularly given its strong connection to chronic diseases such as diabetes, cancer, and cardiovascular conditions. Monitoring dietary behavior is crucial for designing effective interventions that help decrease obesity prevalence and promote healthy lifestyles. However, traditional dietary tracking methods are limited by participant burden and recall bias. Exploring microlevel eating activities, such as meal duration and chewing frequency, in addition to eating episodes, is crucial due to their substantial relation to obesity and disease risk.

Authors

  • Simon Stankoski
    Department of Intelligent Systems, Jožef Stefan Institute, 1000 Ljubljana, Slovenia.
  • Ivana Kiprijanovska
    Department of Intelligent Systems, Jožef Stefan Institute, 1000 Ljubljana, Slovenia.
  • Martin Gjoreski
    Department of Intelligent Systems, Jožef Stefan Institute, Jožef Stefan International Postgraduate School, Jamova cesta 39, Ljubljana, Slovenia. Electronic address: martin.gjoreski@ijs.s.
  • Filip Panchevski
    Emteq Ltd., Brighton, United Kingdom.
  • Borjan Sazdov
    Emteq Ltd., Brighton, United Kingdom.
  • Bojan Sofronievski
    Emteq Ltd., Brighton, United Kingdom.
  • Andrew Cleal
    Emteq Ltd., Brighton, United Kingdom.
  • Mohsen Fatoorechi
    Emteq Ltd., Brighton, United Kingdom.
  • Charles Nduka
    Emteq Ltd., Brighton, United Kingdom.
  • Hristijan Gjoreski
    Department of Intelligent Systems, Jožef Stefan Institute, Jožef Stefan International Postgraduate School, Jamova cesta 39, Ljubljana, Slovenia. Electronic address: hristijan.gjoreski@ijs.s.