Predicting "about-To-eat" moments for just-in-Time eating intervention

Tauhidur Rahman, Mary Czerwinski, Ran Gilad-Bachrach, Paul Johns

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Various wearable sensors capturing body vibration, jaw movement, hand gesture, etc., have shown promise in detecting when one is currently eating. However, based on existing literature and user surveys conducted in this study, we argue that a Just-in-Time eating intervention, triggered upon detecting a current eating event, is sub-optimal. An eating intervention triggered at "About-To-Eat" moments could provide users with a further opportunity to adopt a better and healthier eating behavior. In this work, we present a wearable sensing framework that predicts "About-To-Eat" moments and the "Time until the Next Eating Event". The wearable sensing framework consists of an array of sensors that capture physical activity, location, heart rate, electrodermal activity, skin temperature and caloric expenditure. Using signal processing and machine learning on this raw multimodal sensor stream, we train an "Aboutto-Eat" moment classifier that reaches an average recall of 77%. The "Time until the Next Eating Event" regression model attains a correlation coefficient of 0.49. Personalization further increases the performance of both of the models to an average recall of 85% and correlation coefficient of 0.65. The contributions of this paper include user surveys related to this problem, the design of a system to predict about to eat moments and a regression model used to train multimodal sensory data in real time for potential eating interventions for the user.

Original languageEnglish
Title of host publicationDH 2016 - Proceedings of the 2016 Digital Health Conference
PublisherAssociation for Computing Machinery, Inc
Pages141-150
Number of pages10
ISBN (Electronic)9781450342247
DOIs
StatePublished - 11 Apr 2016
Externally publishedYes
Event6th International Conference on Digital Health, DH 2016 - Montreal, Canada
Duration: 11 Apr 201613 Apr 2016

Publication series

NameDH 2016 - Proceedings of the 2016 Digital Health Conference

Conference

Conference6th International Conference on Digital Health, DH 2016
Country/TerritoryCanada
CityMontreal
Period11/04/1613/04/16

Keywords

  • Eating Habit Modeling
  • Just-in-Time Eating Intervention
  • Next Eating Event Prediction

Fingerprint

Dive into the research topics of 'Predicting "about-To-eat" moments for just-in-Time eating intervention'. Together they form a unique fingerprint.

Cite this