Should we use consumer-grade activity tracker data to understand population physical activity patterns?

Jacqueline L. Mair*, Lawrence D. Hayes, Amy K. Campbell, Nicholas Sculthorpe

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Researchers, practitioners, and public health organisations from around the world are becoming increasingly interested in using data from wearable activity trackers, from companies such as Fitbit Inc, Garmin Ltd, Xiaomi, and Apple Inc, to measure physical activity. Indeed, large-scale, easily accessible, and autonomous data collection concerning physical activity as well as other health behaviours is becoming ever more attractive. There are several benefits of using wearable activity trackers to collect physical activity data, including the ability to obtain big data, retrospectively as well as prospectively, to understand individual level physical activity patterns over time and in response to natural events. However, there are challenges related to representativeness, data access, and proprietary algorithms that, at present, limit the utility of this data in understanding population-level physical activity. In this brief report we aim to highlight the benefits, as well as the limitations, of using existing data from wearable activity trackers to understand large-scale physical activity patterns and stimulate discussion amongst the scientific community on what the future holds with respect to physical activity measurement and surveillance.
Original languageEnglish
Pages (from-to)1-5
Number of pages5
JournalJournal for the Measurement of Physical Behaviour
Publication statusPublished - 25 Oct 2021


  • m-health
  • quantified-self
  • big data
  • surveillance
  • wearables


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