Estimating physical activity in youth using an ankle accelerometer
Crouter, 2018
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Last update: January 15, 2022. Updates will occur every 3 months.
Description
Description
A 2-regression model to predict METs was developed for an ankle-worn ActiGraph in children using vector magnitude counts/5-s. Root Mean Square Error (RMSE) was 1.34 METs and mean bias was 0.42 METs.
Development/Validation
Development/Validation
Sample: 181 (97 males) healthy children, 8-15 years of age
Setting: Laboratory
Activities: Active video games, activities of daily living, overground/self-paced walking and running, sports/exercise, stationary
Criterion: Cosmed K4b2 (VO2)
Accelerometer(s): ActiGraph GT3X or GT3X+ on dominant ankle
Validation approach: Cross-validation using additional visit by sub-sample of participants who participated in free-play at the university or their school
Instructions
Instructions
The coefficient of variation (CV) in vector magnitude counts/5-s (square root of the sum of the squared counts in each axis) for each 5-second epoch and all possible combinations of the surrounding eleven 5-sec epochs is calculated (12 total combinations). For example, the CV is calculated for the 5-sec epoch of interest and 1) the 11 5-s epochs before, 2) the 10 5-s epochs before and one 5-s epoch after, and 3) the nine 5-s epochs before and two 5-s epochs after, and so on. Then, the lowest CV for each 5-s epoch is used to determine the appropriate equation for predicting METs/min.
Source Information
Source Information
Reference:
Crouter, S. E., Oody, J. F., & Bassett Jr, D. R. (2018). Estimating physical activity in youth using an ankle accelerometer. Journal of Sports Sciences, 36(19), 2265-2271. https://doi.org/10.1080/02640414.2018.1449091 Link to Paper
Corresponding author: Scott Crouter, scrouter@utk.edu
Contact
Contact
Kimberly Clevenger at accelerometerrepository@gmail.com
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