Published on in Vol 10, No 2 (2022): February
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/30211, first published
.
![Validity and Feasibility of the Monitoring and Modeling Family Eating Dynamics System to Automatically Detect In-field Family Eating Behavior: Observational Study Validity and Feasibility of the Monitoring and Modeling Family Eating Dynamics System to Automatically Detect In-field Family Eating Behavior: Observational Study](https://asset.jmir.pub/assets/2961a49332d8808d68fc0ddb7348a31b.png 480w,https://asset.jmir.pub/assets/2961a49332d8808d68fc0ddb7348a31b.png 960w,https://asset.jmir.pub/assets/2961a49332d8808d68fc0ddb7348a31b.png 1920w,https://asset.jmir.pub/assets/2961a49332d8808d68fc0ddb7348a31b.png 2500w)
Journals
- Wang L, Chan V, Allman-Farinelli M, Davies A, Wellard-Cole L, Rangan A. Wearable Cameras Reveal Large Intra-Individual Variability in Timing of Eating among Young Adults. Nutrients 2022;14(20):4349 View
- Chan V, Davies A, Wellard-Cole L, Allman-Farinelli M. The energy density of meals and snacks consumed by young Australian adults (18–30 years old) are influenced by preparation location but not screen use nor social interactions: findings from the MYMeals wearable camera study. Journal of Nutritional Science 2022;11 View
- O'Connor S, O’Connor L, Higgins K, Bell B, Krueger E, Rawal R, Hartmuller R, Reedy J, Shams-White M. Conceptualization and Assessment of 24-H Timing of Eating and Energy Intake: A Methodological Systematic Review of the Chronic Disease Literature. Advances in Nutrition 2024;15(3):100178 View