This paper is in the following e-collection/theme issue:

Ecological Momentary Assessment (EMA) (309) Innovations and Technology for Healthy Eating Education (414) Instruments and Questionnaires for Nutrition and Food Intake (166)

Published on in Vol 8, No 12 (2020): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/20625, first published .
A Real-Time Eating Detection System for Capturing Eating Moments and Triggering Ecological Momentary Assessments to Obtain Further Context: System Development and Validation Study

A Real-Time Eating Detection System for Capturing Eating Moments and Triggering Ecological Momentary Assessments to Obtain Further Context: System Development and Validation Study

A Real-Time Eating Detection System for Capturing Eating Moments and Triggering Ecological Momentary Assessments to Obtain Further Context: System Development and Validation Study

Authors of this article:

Mehrab Bin Morshed1 Author Orcid Image ;   Samruddhi Shreeram Kulkarni1 Author Orcid Image ;   Richard Li2 Author Orcid Image ;   Koustuv Saha1 Author Orcid Image ;   Leah Galante Roper1 Author Orcid Image ;   Lama Nachman3 Author Orcid Image ;   Hong Lu3 Author Orcid Image ;   Lucia Mirabella4 Author Orcid Image ;   Sanjeev Srivastava4 Author Orcid Image ;   Munmun De Choudhury1 Author Orcid Image ;   Kaya de Barbaro5 Author Orcid Image ;   Thomas Ploetz1 Author Orcid Image ;   Gregory D Abowd1 Author Orcid Image
Article Authors Cited by (12) Tweetations (1) Metrics

Journals

  1. Morshed M, Kulkarni S, Saha K, Li R, Roper L, Nachman L, Lu H, Mirabella L, Srivastava S, de Barbaro K, de Choudhury M, Plötz T, Abowd G. Food, Mood, Context: Examining College Students’ Eating Context and Mental Well-being. ACM Transactions on Computing for Healthcare 2022;3(4):1 View
  2. Bell B, Alam R, Mondol A, Ma M, Emi I, Preum S, de la Haye K, Stankovic J, Lach J, Spruijt-Metz D. Validity and Feasibility of the Monitoring and Modeling Family Eating Dynamics System to Automatically Detect In-field Family Eating Behavior: Observational Study. JMIR mHealth and uHealth 2022;10(2):e30211 View
  3. Bangamuarachchi W, Chamantha A, Meegahapola L, Ruiz-Correa S, Perera I, Gatica-Perez D. Sensing Eating Events in Context: A Smartphone-Only Approach. IEEE Access 2022;10:61249 View
  4. De Calheiros Velozo J, Vaessen T, Lafit G, Claes S, Myin‐Germeys I. Is daily‐life stress reactivity a measure of stress recovery? An investigation of laboratory and daily‐life stress. Stress and Health 2023;39(3):638 View
  5. Wei B, Zhang S, Diao X, Xu Q, Gao Y, Alshurafa N. An End-to-End Energy-Efficient Approach for Intake Detection With Low Inference Time Using Wrist-Worn Sensor. IEEE Journal of Biomedical and Health Informatics 2023;27(8):3878 View
  6. Gligorić K, Zbinden R, Chiolero A, Kıcıman E, White R, Horvitz E, West R. Measuring and shaping the nutritional environment via food sales logs: case studies of campus-wide food choice and a call to action. Frontiers in Nutrition 2024;11 View
  7. Smith A, Azeem M, Odhiambo C, Wright P, Diktas H, Upton S, Martin C, Froeliger B, Corbett C, Valafar H. Toward Concurrent Identification of Human Activities with a Single Unifying Neural Network Classification: First Step. Sensors 2024;24(14):4542 View
  8. Fernandes G, Zheng J, Pedram M, Romano C, Shahabi F, Rothrock B, Cohen T, Zhu H, Butani T, Hester J, Katsaggelos A, Alshurafa N. HabitSense: A Privacy-Aware, AI-Enhanced Multimodal Wearable Platform for mHealth Applications. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2024;8(3):1 View

Books/Policy Documents

  1. Cychosz M, Cristia A. New Methods and Approaches for Studying Child Development. View