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M2FED: Monitoring and Modeling Family Eating Dynamics: Poster Abstract

Published: 14 November 2016 Publication History

Abstract

The obesity epidemic is the primary cause of recent increases in heart disease, diabetes, cancer, and other diseases that place an untenable strain on healthcare and public health. One of the primary behavioral causes, i.e. dietary intake, is a behavior that science has had little success in understanding, much less affecting. Current behavioral science suggests that family eating dynamics (FED) have high potential to impact child and parent dietary intake and obesity rates. In contrast to traditional obesity related approaches that focus on dietary intakes (e.g., what and how much is being eaten), FED based approaches focus on family mealtime and home food environment (e.g., who is eating, when, where, with whom, interpersonal stress) for modeling behavior and providing feedback that has potential for successful behavior modification. This poster briefly presents M2FED, an integrated system for monitoring and modeling FED. The system is under development, and it consists of in-situ and wearable sensors, and smartphones that collect synchronized real-time FED data used to iteratively develop dynamic, contextualized FED models.

References

[1]
Donna Spruijt-Metz et al. Building new computational models to support health behavior change and maintenance: new opportunities in behavioral research. Translational behavioral medicine, 5(3):335--346, 2015.
[2]
Edison Thomaz et al. A practical approach for recognizing eating moments with wrist-mounted inertial sensing. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pages 1029--1040. ACM, 2015.

Cited By

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  • (2022)Out-of-the-Box Deployment to Support Research on In-Home Care of Alzheimer’s PatientsIEEE Pervasive Computing10.1109/MPRV.2021.310688521:1(37-47)Online publication date: 1-Jan-2022
  • (2022)Perspective: A Framework for Addressing Dynamic Food Consumption ProcessesAdvances in Nutrition10.1093/advances/nmab15613:4(992-1008)Online publication date: Jul-2022
  • (2021)Validity and Feasibility of the Monitoring and Modeling Family Eating Dynamics (M2FED) System to Automatically Detect In-Field Family Eating Behavior: Observational Study (Preprint)JMIR mHealth and uHealth10.2196/30211Online publication date: 10-May-2021
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cover image ACM Conferences
SenSys '16: Proceedings of the 14th ACM Conference on Embedded Network Sensor Systems CD-ROM
November 2016
398 pages
ISBN:9781450342636
DOI:10.1145/2994551
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 November 2016

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Cited By

View all
  • (2022)Out-of-the-Box Deployment to Support Research on In-Home Care of Alzheimer’s PatientsIEEE Pervasive Computing10.1109/MPRV.2021.310688521:1(37-47)Online publication date: 1-Jan-2022
  • (2022)Perspective: A Framework for Addressing Dynamic Food Consumption ProcessesAdvances in Nutrition10.1093/advances/nmab15613:4(992-1008)Online publication date: Jul-2022
  • (2021)Validity and Feasibility of the Monitoring and Modeling Family Eating Dynamics (M2FED) System to Automatically Detect In-Field Family Eating Behavior: Observational Study (Preprint)JMIR mHealth and uHealth10.2196/30211Online publication date: 10-May-2021
  • (2020)Automatic, wearable-based, in-field eating detection approaches for public health research: a scoping reviewnpj Digital Medicine10.1038/s41746-020-0246-23:1Online publication date: 13-Mar-2020
  • (2019)Sensing eating mimicry among family membersTranslational Behavioral Medicine10.1093/tbm/ibz0519:3(422-430)Online publication date: 16-May-2019
  • (2017)Smartphone-based Qualitative Analyses of Social Activities During Family TimeProceedings of the First International Workshop on Human-centered Sensing, Networking, and Systems10.1145/3144730.3144735(49-54)Online publication date: 5-Nov-2017
  • (2017)M^2G: A Monitor of Monitoring Systems with Ground Truth Validation Features for Research-Oriented Residential Applications2017 IEEE 14th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)10.1109/MASS.2017.107(10-18)Online publication date: Oct-2017

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