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Classification of physical activity intensities using a wrist‐worn accelerometer in 8–12‐year‐old children
Author(s) -
Chandler J. L.,
Brazendale K.,
Beets M. W.,
Mealing B. A.
Publication year - 2016
Publication title -
pediatric obesity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.226
H-Index - 69
eISSN - 2047-6310
pISSN - 2047-6302
DOI - 10.1111/ijpo.12033
Subject(s) - accelerometer , medicine , wrist , receiver operating characteristic , population , physical activity , regression analysis , physical medicine and rehabilitation , statistics , mathematics , surgery , computer science , environmental health , operating system
Summary 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 R eceiver 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 R 2 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.