Journal of Applied Physiology AJP: Gastrointestinal and Liver Physiology
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J Appl Physiol (December 1, 2005). doi:10.1152/japplphysiol.00818.2005
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Submitted on July 11, 2005
Accepted on December 1, 2005

A Novel Method for Using Accelerometer Data to Predict Energy Expenditure

Scott E. Crouter1*, Kurt G. Clowers1, and David R. Bassett, Jr.1

1 Department of Exercise, Sport, and Leisure Studies, The University of Tennessee, Knoxville, TN, USA

* To whom correspondence should be addressed. E-mail: sec62{at}cornell.edu.

The purpose of this study was to develop a new 2-regression model relating Actigraph activity counts to EE over a wide range of physical activities. Forty-eight participants (age: 35 ± 11.4 yrs) 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 randomly selected for the development of the new equation and 15 tests were used to cross-validate 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 seconds were calculated to determine if the activity was walking/running, or some other activity. If the CV was ≤ 10 then a walk/run regression equation was used, while if the CV was > 10 a lifestyle/leisure time physical activity (LTPA) 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 METs of measured METs for each of the activities performed (P ≥ 0.05), which was a substantial improvement over the single regression models. The new algorithm is more accurate for the prediction of EE than currently published regression equations using the Actigraph accelerometer.




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