Field Validation of the MTI Actigraph and BodyMedia Armband Monitor Using the IDEEA Monitor

TLDR

Accelerometers hold promise for improving free‑living physical activity and energy expenditure estimates, but differing calibration equations and cut‑off points make it hard to identify the most accurate processing method. This study compared the accuracy of existing calibration equations and algorithms for the MTI Actigraph and Sensewear Pro II armband monitors. Thirty college‑age participants wore both devices during normal daily activities while their energy expenditure and activity were simultaneously measured with the IDEEA monitor as a criterion. The MTI equations produced mean differences of −1.10 to 0.46 METS, the SP2 equations were within 0.10 METS of the IDEEA, and the Matthews MTI cut‑off of 760 counts/min together with the new SP2 equation yielded the lowest PA estimation errors and highest correlations, indicating they are the most accurate indicators.

Abstract

Abstract Objective: Accelerometers offer considerable promise for improving estimates of physical activity (PA) and energy expenditure (EE) in free‐living subjects. Differences in calibration equations and cut‐off points have made it difficult to determine the most accurate way to process these data. The objective of this study was to compare the accuracy of various calibration equations and algorithms that are currently used with the MTI Actigraph (MTI) and the Sensewear Pro II (SP2) armband monitor. Research Methods and Procedures: College‐age participants ( n = 30) wore an MTI and an SP2 while participating in normal activities of daily living. Activity patterns were simultaneously monitored with the Intelligent Device for Estimating Energy Expenditure and Activity (IDEEA) monitor to provide an accurate estimate (criterion measure) of EE and PA for this field‐based method comparison study. Results: The EE estimates from various MTI equations varied considerably, with mean differences ranging from −1.10 to 0.46 METS. The EE estimates from the two SP2 equations were within 0.10 METS of the value from the IDEEA. Estimates of time spent in PA from the MTI and SP2 ranged from 34.3 to 107.1 minutes per day, while the IDEEA yielded estimates of 52 minutes per day. Discussion: The lowest errors in estimation of time spent in PA and the highest correlations were found for the new SP2 equation and for the recently proposed MTI cut‐off point of 760 counts/min (Matthews, 2005). The study indicates that the Matthews MTI cut‐off point and the new SP2 equation provide the most accurate indicators of PA.