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A Method for Quantifying Upper Limb Performance in Daily Life Using Accelerometers
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Validating the Sedentary Sphere method in children: Does wrist or accelerometer brand matter?

Liezel Hurter1, Alex V Rowlands2,3,4, Stuart J Fairclough5

  • 1a Physical Activity Exchange, Research Institute of Sport and Exercise Sciences , Liverpool John Moores University , Liverpool , UK.

Journal of Sports Sciences
|April 24, 2019
PubMed
Summary

The Sedentary Sphere method accurately classifies children's posture using wrist accelerometers (ActiGraph and GENEActiv) for group analysis. Further algorithm refinement is needed for precise individual posture detection.

Keywords:
Wearable technologyactivity classificationsedentary behaviour

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Area of Science:

  • Pediatric physical activity monitoring
  • Biomedical engineering
  • Wearable sensor technology

Background:

  • Accurate measurement of sedentary behavior and posture is crucial for understanding child health.
  • Wrist-worn accelerometers offer a practical method for objective physical activity assessment in children.
  • Validation of posture classification algorithms is essential for reliable data.

Purpose of the Study:

  • To validate the Sedentary Sphere posture classification algorithm using wrist-worn accelerometers (ActiGraph GT9X and GENEActiv) in children.
  • To assess the accuracy and agreement of posture classification between different accelerometer brands and placements.
  • To evaluate the Sedentary Sphere's performance during both prescribed activities and free-living conditions.

Main Methods:

  • Twenty-seven 9-10-year-old children participated in laboratory-based prescribed activities.
  • Children wore ActiGraph GT9X and GENEActiv accelerometers on both wrists, and activPAL on the thigh.
  • An independent sample of 21 children underwent two days of free-living monitoring with wrist accelerometers and activPAL.

Main Results:

  • Posture classification accuracy was high and similar across accelerometer brands (77-79%) for prescribed activities.
  • Posture estimates showed high equivalence between wrists within and between accelerometer brands (ICC > 0.78).
  • Free-living agreement with activPAL was 77%, though sedentary time was underestimated by 7-10%.

Conclusions:

  • The Sedentary Sphere method shows promise for classifying posture from wrist-worn accelerometers in children at a group level.
  • Validation confirms good agreement between ActiGraph and GENEActiv devices for posture estimation.
  • Improvements to the algorithm are necessary to enhance individual-level sedentary time accuracy.