Classification of physical activity intensities using a wrist-worn accelerometer in 8-12-year-old children

Pediatr Obes. 2016 Apr;11(2):120-7. doi: 10.1111/ijpo.12033. Epub 2015 Apr 20.

Abstract

Background: Population-specific accelerometer cut-points are required to accurately determine the accumulation of physical activity of various intensities.

Objectives: A calibration study was conducted (i) to determine the cut-points for the ActiGraph GT3X+, non-dominant, wrist-mounted accelerometer in children aged 8-12 years and (ii) to compare classification accuracies among the accelerometer's three axes and vector magnitude (VM) values.

Methods: Forty-five children aged 8-12 years performed up to seven activities while wearing accelerometers on their non-dominant wrist. Activities were performed in a summer day camp setting, represented free-living activities, and lasted for 10 min with minutes 5-8.5 used for analysis. Direct observation and percentage of heart rate reserve were used to determine activity intensity.

Results: Receiver operator characteristic (ROC) analyses resulted in area under the curve values of all three axes and VM ranging 0.82-0.89, 0.80-0.83, 0.62-0.67 and 0.86-0.89 for light, moderate, vigorous and moderate-to-vigorous activity intensities. Additionally, regression analyses resulted in prediction equations with R2 values ranging from 0.70 to 0.77.

Conclusion: Results found comparable activity intensity classification accuracies from the ActiGraph GT3X+ wrist-worn accelerometer to previously published studies. Based on ROC and regression analyses, activity intensities can be distilled from this accelerometer using axis 1, axis 2 or VM values with similar classification accuracy.

Keywords: Accelerometry; activity; calibration; children.

Publication types

  • Multicenter Study
  • Observational Study

MeSH terms

  • Accelerometry / instrumentation*
  • Accelerometry / methods
  • Calibration
  • Child
  • Energy Metabolism / physiology*
  • Female
  • Heart Rate / physiology*
  • Humans
  • Male
  • Motor Activity / physiology*
  • Physical Fitness / physiology*
  • ROC Curve
  • Regression Analysis
  • South Carolina / epidemiology
  • Wrist