Comparison of nine theoretical models for estimating the mechanical power output in cycling. Issue 8 (6th March 2007)

• Record Type: Journal Article
• Authors: González-Haro, Carlos; Galilea Ballarini, P A; Soria, M; Drobnic, F; Escanero, J F
• Is Part Of: British journal of sports medicine. Volume 41:Issue 8(2007)
• Page Start: 506
• Page End: 509
• Publication Date: 2007-03-06
• Subjects: MSEP, mean squared error of prediction -- PPO, peak power output -- RE, random error -- SE, systematic error -- Vo2max, maximal oxygen uptake; cycling -- mechanical power output -- speed -- velodrome -- SRM training system; Sports medicine -- Periodicals; 617.1027
• DOI: 10.1136/bjsm.2006.034934
• Languages: English
• ISSNs: 0306-3674

Abstract

Abstract : Objective: To assess which of the equations used to estimate mechanical power output for a wide aerobic range of exercise intensities gives the closest value to that measured with the SRM training system. Methods: Thirty four triathletes and endurance cyclists of both sexes (mean (SD) age 24 (5) years, height 176.3 (6.6) cm, weight 69.4 (7.6) kg and Vo 2 max 61.5 (5.9) ml/kg/min) performed three incremental tests, one in the laboratory and two in the velodrome. The mean mechanical power output measured with the SRM training system in the velodrome tests corresponding to each stage of the tests was compared with the values theoretically estimated using the nine most referenced equations in literature (Whitt ( Ergonomics 1971;14:419–24); Di Prampero et al ( J Appl Physiol 1979;47:201–6); Whitt and Wilson ( Bicycling science . Cambridge: MIT Press, 1982); Kyle ( Racing with the sun . Philadelphia: Society of Automotive Engineers, 1991:43–50); Menard (First International Congress on Science and Cycling Skills, Malaga, 1992); Olds et al ( J Appl Physiol 1995;78:1596–611; J Appl Physiol 1993;75:730–7); Broker ( USOC Sport Science and Technology Report 1–24, 1994); Candau et al ( Med Sci Sports Exerc 1999;31:1441–7)). This comparison was made using the mean squared error of prediction, the systematic error and the random error. Results: The equations of Candau et al, Di Prampero et al, Olds et al ( J Appl Physiol 1993;75:730–7) and Whitt gave a moderate mean squared error of prediction (12.7%, 21.6%, 13.2% and 16.5%, respectively) and a low random error (0.5%, 0.6%, 0.7% and 0.8%, respectively). Conclusions: The equations of Candau et al and Di Prampero et al give the best estimate of mechanical power output when compared with measurements obtained with the SRM training system.