Use of Heart Rate to Predict Energy Expenditure from Low to High Activity Levels

Abstract This study evaluated the ability to use the relationship between heart rate (HR) and oxygen uptake (V˙O 2 ) to estimate energy expenditure (EE) from low to high physical activity with different HR-based prediction equations. General prediction equations were established based on the individual relations between HR and EE. Possibilities to improve the EE estimation with using alternatives for respective HR were also assessed. The alternatives were % of HR reserve: 100 × [(activity HR - resting HR)/(maximal HR - resting HR)], (HRR), and the difference between activity HR and resting HR (activity HR - resting HR), (HRnet). Forty-two men (age mean 36.5 [sd 7.6] y, BMI 24.5 [2.4] kg × m -2 , V˙O 2 max 45.2 [6.5]) kg × ml × min -1 and 47 women (mean age 37.5 [9.5], BMI 23.3 [3.4], V˙O 2 max 36.3 [5.4]) performed an exercise test consisting of physically low-activity tasks and a maximal treadmill uphill walking test. Respiratory gases were obtained from indirect calorimetry. HR was registered by electrocardiography and EE was calculated from (V˙O 2 ) and carbon dioxide (V˙CO 2 ) production. Generalised linear models with random effects were used for the prediction of EE. EE values of the tests (one value at each intensity level) were predicted in separate models by the respective HR, HRR or HRnet values. The other predictors used in all models were body weight, sex and the intensity of exercise. The standard error of estimate (SEE) was 1.41 kcal × min -1 (5.89 kJ) in the model with HR variable as a predictor, 1.01 kcal × min -1 (4.22 kJ) with HRR variable, and 1.08 (4.51 kJ) with HRnet variable. The results show that the prediction of EE is more accurate if HRR or HRnet are used in prediction equation instead of HR.