For total EE , correlation coefficients were statistically significantly lower in uniaxial compared to multisensor devices .
For active EE , correlations were slightly but not significantly lower in uniaxial compared to triaxial and multisensor devices .
The high level of heterogeneity in the validation studies is only partly explained by the type of activity monitor and the activity monitor outcome .
Triaxial and multisensor devices tend to be more valid monitors .
The assessment of physical activity in healthy population s and in those with chronic diseases is challenging .
The aim of this systematic review was to identify whether available activity monitors ( AM ) have been appropriately vali date d for use in assessing physical activity in these groups .
Validity of estimating minute-by-minute energy expenditure of continuous walking bouts by accelerometry
Background 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 . Methods Thirty 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 GT1 M accelerometer and Cosmed K4b2 portable metabolic system were worn during all activities . Participants were r and omly 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 . Results The 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 ) . Conclusion The 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
For total EE , correlation coefficients were statistically significantly lower in uniaxial compared to multisensor devices .
For active EE , correlations were slightly but not significantly lower in uniaxial compared to triaxial and multisensor devices .
The high level of heterogeneity in the validation studies is only partly explained by the type of activity monitor and the activity monitor outcome .
Triaxial and multisensor devices tend to be more valid monitors .
The assessment of physical activity in healthy population s and in those with chronic diseases is challenging .
The aim of this systematic review was to identify whether available activity monitors ( AM ) have been appropriately vali date d for use in assessing physical activity in these groups .