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Automatic Identification of Physical Activity Type and Duration by Wearable Activity Trackers: A Validation Study.

Diana DornJessica S GorzelitzRonald E GangnonDavid R BellKelli KoltynLisa A Cadmus-Bertram
Published in: JMIR mHealth and uHealth (2019)
In a controlled setting, wearable activity trackers provide accurate recognition of the type of some common physical activities, especially outdoor walking and running and walking on a treadmill. The accuracy of measurement of activity duration varied considerably by activity type and tracker model and was poor for complex sets of activity, such as a run embedded within 2 walking segments.
Keyphrases
  • physical activity
  • mental health
  • machine learning
  • body mass index
  • high resolution
  • deep learning
  • high intensity