PURPOSE: This study was designed to characterize the relative contributions of the current heart rate (HR) and HR in the previous minute to predict energy expenditure (EE) and to model these and other determinants to predict EE during intermittent activity. METHODS: Regularly exercising subjects (N=65, 36+/-9 yr, body mass index (BMI), 23.9+/- 2.5 kg.m) were tested. Body composition and maximal oxygen uptake (& OV0312;O2) were measured. On a separate day, subjects completed 12 x 4-min workloads, separated by 4 x 1-min rest periods, during which HR and & OV0312;O2 were continuously monitored. Using the intermittent activity calibration data, an EE model was developed. For validation, the final model was used to predict EE in a separate sample (N=17), who completed a gym training exercise session. Using the HR data, EE data were estimated using (a) the new model and were compared with (b) a previous model developed using a continuous incremental calibration test. RESULTS: The following variables contributed significantly to the estimation of EE during intermittent activity: age, gender, & OV0312;O2 max, current minute's HR, previous minute's HR, and an interaction variable consisting of previous minute's HR and & OV0312;O2 max. The final model yielded an R of 82% for the comparison of predicted and measured EE. When this model was applied to an independent sample for validation (N=17), improvements in EE prediction, when compared to the existing model (b), were most apparent during free-living non-continuous exercise. CONCLUSION: It is possible to improve the accuracy of predicting EE from HR, by incorporating both & OV0312;O2 max and the previous minute's HR in the prediction model.
PURPOSE: This study was designed to characterize the relative contributions of the current heart rate (HR) and HR in the previous minute to predict energy expenditure (EE) and to model these and other determinants to predict EE during intermittent activity. METHODS: Regularly exercising subjects (N=65, 36+/-9 yr, body mass index (BMI), 23.9+/- 2.5 kg.m) were tested. Body composition and maximal oxygen uptake (& OV0312;O2) were measured. On a separate day, subjects completed 12 x 4-min workloads, separated by 4 x 1-min rest periods, during which HR and & OV0312;O2 were continuously monitored. Using the intermittent activity calibration data, an EE model was developed. For validation, the final model was used to predict EE in a separate sample (N=17), who completed a gym training exercise session. Using the HR data, EE data were estimated using (a) the new model and were compared with (b) a previous model developed using a continuous incremental calibration test. RESULTS: The following variables contributed significantly to the estimation of EE during intermittent activity: age, gender, & OV0312;O2 max, current minute's HR, previous minute's HR, and an interaction variable consisting of previous minute's HR and & OV0312;O2 max. The final model yielded an R of 82% for the comparison of predicted and measured EE. When this model was applied to an independent sample for validation (N=17), improvements in EE prediction, when compared to the existing model (b), were most apparent during free-living non-continuous exercise. CONCLUSION: It is possible to improve the accuracy of predicting EE from HR, by incorporating both & OV0312;O2 max and the previous minute's HR in the prediction model.