WillSense: Adherence barriers for passive sensing systems that track eating behavior

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Energy balance is one component of weight management, but passive objective measures of caloric intake are nonexistent. Given recent success of actigraphy as a passive objective measure of the physical activity construct that relieves participants of the burden of biased self-report, researchers are aiming to find a passive objective measure of caloric intake to improve understanding of problematic eating behaviors in participants with and without obesity. Passive sensing food intake systems have failed to go beyond the lab and into behavioral research in part due to low adherence to wearing passive monitoring systems. This paper presents preliminary results in participants with and without obesity performing structured and unstructured eating experiments to understand wearable adherence as affected by: 1) perceived data privacy; 2) stigma of wearing devices; 3) comfort. Wearables examined include neck- and wrist-worn sensors, and video camera-based systems.

Original languageEnglish (US)
Title of host publicationCHI 2017 Extended Abstracts - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems
Subtitle of host publicationExplore, Innovate, Inspire
PublisherAssociation for Computing Machinery
Pages2329-2336
Number of pages8
ISBN (Electronic)9781450346566
DOIs
StatePublished - May 6 2017
Event2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017 - Denver, United States
Duration: May 6 2017May 11 2017

Publication series

NameConference on Human Factors in Computing Systems - Proceedings
VolumePart F127655

Other

Other2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017
CountryUnited States
CityDenver
Period5/6/175/11/17

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Keywords

  • Comfort
  • Eating detection
  • Passive sensing
  • Privacy
  • Stigma
  • Wearables

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

Cite this

Alharbi, R., Pfammatter, A., Spring, B., & Alshurafa, N. (2017). WillSense: Adherence barriers for passive sensing systems that track eating behavior. In CHI 2017 Extended Abstracts - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems: Explore, Innovate, Inspire (pp. 2329-2336). (Conference on Human Factors in Computing Systems - Proceedings; Vol. Part F127655). Association for Computing Machinery. https://doi.org/10.1145/3027063.3053271