Purpose: Using a larger sample and broader range of activities than most previous investigations of HR monitoring, this study examined the need for individual calibration of the HR-V̇O2 prediction equation, the effect of including low-intensity activities when establishing the HR-V̇O2 equation, comparisons of different methods for calculating HR-V̇O2 prediction equations for maximum energy expenditure (EE) variance, and the effect of these different methods when applied to free-living HR data.
Methods: Forty-three children ages 8 to 12 completed laboratory assessments of the relationship between HR and V̇O2. Different methods of estimating daily EE were applied to free-living HR data collected from 37 of these children.
Results: There was significant individual variation in the HR-V̇O2 prediction equations. HR monitoring predicted V̇O2 during low-intensity activities, below most established cut points. Individual differences persisted during both high- and low-intensity activities. Although a HR-V̇O2 prediction equation generated from the group accounted for 85% of the variance in EE, significant improvements in prediction were achieved with individualized HR-V̇O2 prediction equations that took into account low-intensity activity levels.
Conclusion: Generic equations derived from group data may be suitable for some applications. However, for investigators requiring more precision, individual HR-V̇O2 equations significantly improve prediction.