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Is fitbit fit for sleep-tracking?: sources of measurement errors and proposed countermeasures

Published:23 May 2017Publication History

ABSTRACT

It is now easy to track one's sleep through consumer wearable devices like Fitbit from the comfort of one's home. However, compared to clinical measures, the data generated by such consumer devices is limited in its accuracy. The aim of this paper is to explore how users perceive accuracy issues, possible measurement errors and what can be done to address these issues. Through an interview study with 14 Fitbit users we identified three main sources of errors: (1) lack of definition of sleep metrics, (2) limitations in underlying data collection and processing mechanisms, and (3) lack of rigor in tracking approach. This paper proposes countermeasures to address these issues, both from the aspect of technological advancement and through engaging end-users more closely with their data.

References

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  • Published in

    cover image ACM Other conferences
    PervasiveHealth '17: Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare
    May 2017
    503 pages
    ISBN:9781450363631
    DOI:10.1145/3154862

    Copyright © 2017 Owner/Author

    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: 23 May 2017

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    Overall Acceptance Rate55of116submissions,47%

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