Garmin® Health and ActiGraph™ Collaborate on Wearable Solutions for Clinical Trials
A Refined 2-Regression Model for the ActiGraph Accelerometer
- Published on 05/01/2010
Purpose The purpose of this study was to refine the 2006 Crouter 2-regression model to eliminate the misclassification of walking/running when starting an activity in the middle of a minute on the ActiGraph clock.
Methods Forty-eight participants [mean (sd) age 35 yrs (11.4)] performed 10-min bouts of various activities ranging from sedentary behaviors to vigorous physical activity. Eighteen activities were divided into three routines and 20 participants performed each routine. Participants wore an ActiGraph accelerometer on the hip and a portable indirect calorimeter was used to measure energy expenditure. Forty-five routines were used to develop the refined 2-regression model and 15 routines were used to cross-validate the model. Coefficient of variation (CV) was used to classify each activity as continuous walking/running (CV≤10) or intermittent lifestyle activity (CV>10).
Results An exponential regression equation and a cubic equation using the natural log of the 10-sec counts were developed to predict METs every 10-sec for walking/running and intermittent lifestyle activities, respectively. The refined method examines each 10-sec epoch and all combinations of the surrounding five 10-sec epochs to find the lowest CV. In the cross-validation group, the refined method was not significantly different from measured METs for any activity (P>0.05) except cycling (P<0.05). In addition, the 2006 and refined 2-regression models had similar accuracy and precision for estimating energy expenditure during structured activities.
Conclusion The refined 2-regression model should eliminate the misclassification of transitional minutes when changing activities that start and stop in the middle of a minute on the ActiGraph clock, thus improving the estimate of free-living energy expenditure.
Key Words Motion Sensor, Physical Activity, Oxygen Consumption, Activity Counts Variability Online Abstract: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2891855/
Medicine & Science in Sports & Exercise