Situating Wearables: Smartwatch Use in Context

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

DOI

  • Donald McMillan, Stockholm University, Kista, Sweden
  • ,
  • Barry Brown, Stockholm University
  • ,
  • Airi Lampinen, Stockholm University, Kista, Sweden
  • ,
  • Moira McGregor, Stockholm University, Kista, Sweden
  • ,
  • Eve Hoggan
  • Stefania Pizza, Sapienza University of Rome

This paper studies how context influences smartwatch use. Drawing on 168 hours of video recordings of smartwatch use, we explore the effects of the presence of others, activity, location and time of day on 1, 009 instances of use. Watch interaction is significantly shorter when the user is in conversation, than when alone. Activity also exerts influence-with significantly longer watch use while eating than when socialising or performing domestic tasks. One surprising finding is that length of use is similar at home and work. We note that usage peaks around lunchtime, with an average of 5.3 watch uses per hour throughout a day. We supplement these findings with qualitative analysis of the videos, focusing on how use is modified by the presence of others, and the lack of impact of watch glances on conversation. Watch use is clearly a context-sensitive activity, and in discussion we explore how smartwatches could be designed taking this into consideration.

Original languageEnglish
Title of host publicationCHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems : Explore, Innovate, Inspire
Number of pages13
Place of publicationNew York, NY, USA
PublisherAssociation for Computing Machinery
Publication year2 May 2017
Pages3582-3594
ISBN (print)978-1-4503-4655-9
ISBN (Electronic)9781450346559
DOIs
Publication statusPublished - 2 May 2017
EventCHI 2017 - Denver, United States
Duration: 6 May 201712 May 2017
https://chi2017.acm.org/

Conference

ConferenceCHI 2017
LandUnited States
ByDenver
Periode06/05/201712/05/2017
Internetadresse
SeriesCHI '17

    Research areas

  • smartwatch, video analysis, wearable, Video analysis, Wearable, Smartwatch

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