Abstract
The most promising potential substitutes for respiratory calorimetry are regression equations that relate caloric expenditure to heart rate. This study evaluates multiple regression equations, employing seven indices derived from the time pathway of the heart rate, as a means of increasing the precision of the heart rate method. Regression equations are based on the aggregation of different tasks and/or subjects as well as on the single task and single subject. The multiple regression equations are compared with simple regression equations and with respiratory calorimetry in terms of the errors of estimation that each introduces into the measurement of caloric expenditure. The results show that multiple regression equations based on a single subject and single task are as precise as respiratory calorimetry.
