TY - JOUR
T1 - Improvement of energy expenditure prediction from heart rate during running
AU - Charlot, Keyne
AU - Cornolo, Jeremy
AU - Borne, Rachel
AU - Brugniaux, Julien Vincent
AU - Richalet, Jean-Paul
AU - Chapelot, Didier
AU - Pichon, Aurelien
PY - 2014
Y1 - 2014
N2 - We aimed to develop new equations that predict exercise-induced energy expenditure (EE) more accurately than previous ones during running by including new parameters as fitness level, body composition and/or running intensity in addition to heart rate (HR). Original equations predicting EE were created from data obtained during three running intensities (25%, 50% and 70% of HR reserve) performed by 50 subjects. Five equations were conserved according to their accuracy assessed from error rates, interchangeability and correlations analyses: one containing only basic parameters, two containing VO2max or speed at VO2max and two including running speed with or without HR. Equations accuracy was further tested in an independent sample during a 40 min validation test at 50% of HR reserve. It appeared that: (1) the new basic equation was more accurate than pre-existing equations (R2 0.809 versus. 0,737 respectively); (2) the prediction of EE was more accurate with the addition of VO2max (R2 = 0.879); and (3) the equations containing running speed were the most accurate and were considered to have good agreement with indirect calorimetry. In conclusion, EE estimation during running might be significantly improved by including running speed in the predictive models, a parameter readily available with treadmill or GPS.
AB - We aimed to develop new equations that predict exercise-induced energy expenditure (EE) more accurately than previous ones during running by including new parameters as fitness level, body composition and/or running intensity in addition to heart rate (HR). Original equations predicting EE were created from data obtained during three running intensities (25%, 50% and 70% of HR reserve) performed by 50 subjects. Five equations were conserved according to their accuracy assessed from error rates, interchangeability and correlations analyses: one containing only basic parameters, two containing VO2max or speed at VO2max and two including running speed with or without HR. Equations accuracy was further tested in an independent sample during a 40 min validation test at 50% of HR reserve. It appeared that: (1) the new basic equation was more accurate than pre-existing equations (R2 0.809 versus. 0,737 respectively); (2) the prediction of EE was more accurate with the addition of VO2max (R2 = 0.879); and (3) the equations containing running speed were the most accurate and were considered to have good agreement with indirect calorimetry. In conclusion, EE estimation during running might be significantly improved by including running speed in the predictive models, a parameter readily available with treadmill or GPS.
KW - energy
KW - heart beat
KW - indirect calorimetry
KW - running
UR - http://handle.uws.edu.au:8081/1959.7/uws:36721
U2 - 10.1088/0967-3334/35/2/253
DO - 10.1088/0967-3334/35/2/253
M3 - Article
SN - 0967-3334
VL - 35
SP - 253
EP - 266
JO - Physiological Measurement
JF - Physiological Measurement
IS - 2
ER -