Prediction of energy expenditure from heart rate monitoring during submaximal exercise.

The aims of this study were to quantify the effects of factors such as mode of exercise, body composition and training on the relationship between heart rate and physical activity energy expenditure (measured in kJ x min(-1)) and to develop prediction equations for energy expenditure from heart rate. Regularly exercising individuals (n = 115; age 18-45 years, body mass 47-120 kg) underwent a test for maximal oxygen uptake (VO2max test), using incremental protocols on either a cycle ergometer or treadmill; VO2max ranged from 27 to 81 ml x kg(-1) x min(-1). The participants then completed three steady-state exercise stages on either the treadmill (10 min) or the cycle ergometer (15 min) at 35%, 62% and 80% of VO2max, corresponding to 57%, 77% and 90% of maximal heart rate. Heart rate and respiratory exchange ratio data were collected during each stage. A mixed-model analysis identified gender, heart rate, weight, V2max and age as factors that best predicted the relationship between heart rate and energy expenditure. The model (with the highest likelihood ratio) was used to estimate energy expenditure. The correlation coefficient (r) between the measured and estimated energy expenditure was 0.913. The model therefore accounted for 83.3% (R2) of the variance in energy expenditure in this sample. Because a measure of fitness, such as VO2max, is not always available, a model without VO2max included was also fitted. The correlation coefficient between the measured energy expenditure and estimates from the mixed model without VO2max was 0.857. It follows that the model without a fitness measure accounted for 73.4% of the variance in energy expenditure in this sample. Based on these results, we conclude that it is possible to estimate physical activity energy expenditure from heart rate in a group of individuals with a great deal of accuracy, after adjusting for age, gender, body mass and fitness.