Abstract
BackgroundObjective measurement of physical activity remains an important challenge. For wearable monitors such as accelerometer-based physical activity monitors, more accurate methods are needed to convert activity counts into energy expenditure (EE).PurposeThe purpose of this study was to examine the accuracy of the refined Crouter 2-Regression Model (C2RM) for estimating EE during the transition from rest to walking and walking to rest. A secondary purpose was to determine the extent of overestimation in minute-by-minute EE between the refined C2RM and the 2006 C2RM.MethodsThirty volunteers (age, 28 ± 7.7 yrs) performed 15 minutes of seated rest, 8 minutes of over-ground walking, and 8 minutes of seated rest. An ActiGraph GT1M accelerometer and Cosmed K4b2 portable metabolic system were worn during all activities. Participants were randomly assigned to start the walking bout at 0, 20, or 40 s into the minute (according to the ActiGraph clock). Acceleration data were analyzed by two methods: 2006 Crouter model and a new refined model.ResultsThe 2006 Crouter 2-Regression model over-predicted measured kcal kg-1 hr-1 during the first and last transitional minutes of the 20-s and 40-s walking conditions (P < 0.001). It also over-predicted the average EE for a walking bout (4.0 ± 0.5 kcal kg-1 hr-1), compared to both the measured kcal kg-1 hr-1 (3.6 ± 0.7 kcal kg-1 hr-1) and the refined Crouter model (3.5 ± 0.5 kcal kg-1 hr-1) (P < 0.05).ConclusionThe 2006 Crouter 2-regression model over-predicts EE at the beginning and end of walking bouts, due to high variability in accelerometer counts during the transitional minutes. The new refined model eliminates this problem and results in a more accurate prediction of EE during walking.
Highlights
Objective measurement of physical activity remains an important challenge
Due to the inherent errors in single regression models, researchers have sought to develop other approaches for analyzing accelerometer data. One such approach, developed for use with the ActiGraph accelerometer, is the 2006 Crouter 2-regression model (C2RM), which does not assume a linear relationship between mean counts and metabolic equivalents (METs) for all activities [6]
A secondary purpose was to determine the extent of overestimation in minute-by-minute EE between the refined Crouter 2-Regression Model (C2RM) [7] and the 2006 C2RM [6]
Summary
Objective measurement of physical activity remains an important challenge. For wearable monitors such as accelerometer-based physical activity monitors, more accurate methods are needed to convert activity counts into energy expenditure (EE).Purpose: The purpose of this study was to examine the accuracy of the refined Crouter 2-Regression Model (C2RM) for estimating EE during the transition from rest to walking and walking to rest. A secondary purpose was to determine the extent of overestimation in minute-by-minute EE between the refined C2RM and the 2006 C2RM Accelerometers, such as the ActiGraph or Actical, are often used to provide an objective record of physical activity. Single linear regression equations, regardless of which brand they were developed One such approach, developed for use with the ActiGraph accelerometer, is the 2006 Crouter 2-regression model (C2RM), which does not assume a linear relationship between mean counts and metabolic equivalents (METs) for all activities [6]. Instead, it examines the variability among six consecutive 10-s epochs within a oneminute period to predict EE. If there is a low variability among the 10-s epochs, a walk/run regression equation is used, but if the variability among 10-s epochs is high, a different equation is used for intermittent lifestyle activities
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