It is suggested that triaxial accelerometers (RT3) are superior to single-plane accelerometers for predicting energy expenditure (EE).
To compare the RT3 uniaxial and triaxial prediction of activity EE (AEE) during treadmill activities (TM) and activities of daily living (ADL).
Two hundred and twelve subjects (aged 20-60 yr) completed TM speeds of 1.34, 1.56, and 2.23 m·s−1 at 0% and 3% grades, stair ascent/descent, moving a box, and two randomly assigned ADL. Subjects wore a portable indirect calorimeter to measure EE to calculate AEE by subtracting resting metabolic rate. Acceleration counts in the vertical (V), medial-lateral, and anterior-posterior planes were collected in a single RT3 secured to the hip. Predicted AEE (RT3AEE) was estimated from vector magnitude (VM) counts using a proprietary algorithm. A paired t-test compared RT3AEE versus AEE. The relationship among V and VM counts and AEE was examined using linear regression analyses.
RT3 overestimated AEE for all activities combined, overestimated for TM (9.0%), and underestimated for ADL (34.3%; P < 0.001). The R 2 values between RT3AEE and AEE for TM and ADL were R 2 = 0.78 and R 2 = 0.15, respectively. The RT3 underestimated activity with greater upper body movements by 24.4%-64.5% (P < 0.001). V and VM counts were similarly related to AEE (R 2 = 0.35) and RT3AEE (R 2 = 0.83-0.89).
Although the RT3 did not accurately predict AEE from accelerometer counts, stronger relationships existed between predicted and measured AEE for TM compared with ADL. Compared with V counts, using VM counts to predict AEE did not significantly improve the relationship between counts and AEE. Analytic techniques beyond linear regression with VM as a covariate or with counts from each axis entering the model separately may improve estimates of AEE from triaxial accelerometers.
1Department of Kinesiology, University of Massachusetts, Amherst, MA; and 2Department of Math and Statistics, University of Massachusetts, Amherst, MA
Address for correspondence: Patty S. Freedson, Ph.D., Department of Kinesiology, University of Massachusetts, 30 Eastman Lane, 162 Totman Bldg, Amherst, MA 01003; E-mail: email@example.com.
Submitted for publication January 2009.
Accepted for publication April 2009.