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Comparison of nine theoretic models estimating the mechanical power output in cycling.
  1. Carlos González-Haro (ghcarlos{at}gmail.com)
  1. Physical Activity and Sports Professional Medicine School, University of Barcelona., Spain
    1. Pedro A. Galilea
    1. Department of sports sciences, High Performance Centre (CAR),, Spain
      1. Marisol Soria (msoria{at}unizar.es)
      1. Department of Pharmacology and Physiology, Faculty of Medicine, University of Zaragoza., Spain
        1. Franchek Drobnic (drobnic{at}car.edu)
        1. Department of sports sciences, High Performance Centre (CAR),, Spain
          1. Jesús F. Escanero (escanero{at}unizar.es)
          1. Department of Pharmacology and Physiology, Faculty of Medicine, University of Zaragoza., Spain

            Abstract

            Objective: The aim of this study was to assess which of the equations that estimate the mechanical power output for all the aerobic range of exercise intensities adapts best to the measurements obtained with the SRM training system (Schoberer Rad Messtechnik®, Germany).

            Methods: Thirty-four triathletes and endurance modality cyclists of both sexes (24 ± 5 yrs, 176.3 ± 6.6 cm, 69.4 ± 7.6 kg and 67 ± 6 mL•kg−1•min−1) performed three incremental tests, one in laboratory and two in velodrome. The average mechanical power output measured by means of the SRM training system in the velodrome tests corresponding to each one of the stages of the tests was compared with the values theoretically estimated by the 9 most referenced equations in literature (Whitt,[11] Di Prampero et al.,[12] Whitt and Wilson,[13] Kyle,[14] Menard,[15] Olds et al.,[16, 17] Basset et al.,[6] Candau et al.,[18]). This comparison was made by means of the mean squared error of prediction (MSEP), the systematic error (SE) and the random error (RE).

            Results: The results showed that, for the estimation of the mechanical power output, the equations of Candau et al.,[18] Di Prampero et al.,[12] Olds et al.[17] and Whitt[11] presented a moderate MSEP (12.7, 21.6, 13.2 and 16.5 %, respectively) and a low RE (0.5, 0.6, 0.7, 0.8 %, respectively).

            Conclusions: The equations proposed by Candau et al.[18] and Di Prampero et al.[12] are the ones that estimate the mechanical power output the best when comparing with SRM training system measurements.

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