Published on in Vol 24, No 3 (2022): March
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/27934, first published
.

Journals
- Wang L, Allman-Farinelli M, Hekler E, Rangan A. A Scoping Review of Sensor-Based Capture of Eating and Drinking Occasions That Could Be Used for Enhancing Personalized Nutrition Interventions in Real Time. Advances in Nutrition 2026;17(2):100575 View
- Shirgaonkar Y, Gokhale D. AI and machine learning for early identification of eating disorders: a narrative review and Indian contextual insights. Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity 2026;31(1) View
- Fang J, Chan K, Zhang X, Wang Y, Gao M, Peng L, Li J, Zhan Z, Zhao Z, Shi Y. Earinter: A Closed-Loop System for Eating Pace Regulation with Just-in-Time Intervention Using Commodity Earbuds. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2026;10(3):1 View
Conference Proceedings
- Chung Y, Nikooienejad A, Zhang B. 2022 IEEE International Conference on Big Data (Big Data). Automatic Eating Behavior Detection from Wrist Motion Sensor Using Bayesian, Gradient Boosting, and Topological Persistence Methods View
- Santoso K, Maharani M, Sidharta S. 2024 International Conference on Information Management and Technology (ICIMTech). Identifying Abnormal Eating Behavior Patterns with Machine Learning for Early Detection of Eating Disorders: A Systematic Literature Review View
