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 .
A novel method for using accelerometer data to predict energy expenditure.
The purpose of this study was to develop a new two-regression model relating Actigraph activity counts to energy expenditure over a wide range of physical activities . Forty-eight participants [ age 35 yr ( 11.4 ) ] performed various activities chosen to represent sedentary , light , moderate , and vigorous intensities . Eighteen activities were split into three routines with each routine being performed by 20 individuals , for a total of 60 tests . Forty-five tests were r and omly selected for the development of the new equation , and 15 tests were used to cross-vali date the new equation and compare it against already existing equations . During each routine , the participant wore an Actigraph accelerometer on the hip , and oxygen consumption was simultaneously measured by a portable metabolic system . For each activity , the coefficient of variation ( CV ) for the counts per 10 s was calculated to determine whether the activity was walking/running or some other activity . If the CV was < or=10 , then a walk/run regression equation was used , whereas if the CV was > 10 , a lifestyle/leisure time physical activity regression was used . In the cross-validation group , the mean estimates using the new algorithm ( 2-regression model with an inactivity threshold ) were within 0.75 metabolic equivalents ( METs ) of measured METs for each of the activities performed ( P > or= 0.05 ) , which was a substantial improvement over the single-regression models . The new algorithm is more accurate for the prediction of energy expenditure than currently published regression equations using the Actigraph accelerometer
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 .