Designing for Triggering Self-Investigations and Reflections on Factors Related to Sleep Health

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

Abstract

While sleep health is increasingly becoming important to many people, it is challenging to maintain good sleep quality. Because sleep can be affected by many internal and external factors, which may differ among individuals, it is therefore important to support people to explore and reflect on what factors truly affect their sleep as most existing sleep self-tracking tools mainly focus on showing how individuals slept. In this study, we developed two design probes to support users to investigate personal sleep factors through self-experimenting and reflection. The tangible probe enables individuals to track three personal sleep factors flexibly, while the digital visualization one provides weekly reports of their sleep together with the three tracked factors. We conducted a preliminary field study with five participants over four weeks. The results show that our designs could support users to investigate their personal concerned sleep factors in terms of the causal relationship with the subjective sleep quality.

Original languageEnglish
Title of host publicationNordiCHI 2020 - Proceedings of the 11th Nordic Conference on Human-Computer Interaction
Subtitle of host publicationShaping Experiences, Shaping Society
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450375795
DOIs
Publication statusPublished - 25 Oct 2020
Event11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society, NordiCHI 2020 - Virtual, Online, Estonia
Duration: 25 Oct 202029 Oct 2020

Publication series

NameACM International Conference Proceeding Series

Conference

Conference11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society, NordiCHI 2020
CountryEstonia
CityVirtual, Online
Period25/10/2029/10/20

Keywords

  • Data visualization
  • Personal informatics
  • Quantified self
  • Self-tracking
  • Sleep health
  • Sleep tracking

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