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Published on: February 5, 2020
Experimental evaluation of the power balance model of speed skating
Jos J de Koning1, Carl Foster, Joanne Lampen
1Faculty of Human Movement Sciences, Vrije Universiteit Amsterdam, Van der Boerststraat 9, 1081 BT Amsterdam, The Netherlands. j_j_de_koning@fbw.vu.nl
Abstract:
Prediction of speed skating performance with a power balance model requires assumptions about the kinetics of energy production, skating efficiency, and skating technique. The purpose of this study was to evaluate these parameters during competitive imitations for the purpose of improving model predictions. Elite speed skaters (n = 8) performed races and submaximal efficiency tests. External power output (P(o)) was calculated from movement analysis and aerodynamic models and ice friction measurements. Aerobic kinetics was calculated from breath-by-breath oxygen uptake (Vo(2)). Aerobic power (P(aer)) was calculated from measured skating efficiency. Anaerobic power (P(an)) kinetics was determined by subtracting P(aer) from P(o). We found gross skating efficiency to be 15.8% (1.8%). In the 1,500-m event, the kinetics of P(an) was characterized by a first-order system as P(an) = 88 + 556e(-0.0494t) (in W, where t is time). The rate constant for the increase in P(aer) was -0.153 s(-1), the time delay was 8.7 s, and the peak P(aer) was 234 W; P(aer) was equal to 234[1 - e(-0.153(t-8.7))] (in W). Skating position changed with preextension knee angle increasing and trunk angle decreasing throughout the event. We concluded the pattern of P(aer) to be quite similar to that reported during other competitive imitations, with the exception that the increase in P(aer) was more rapid. The pattern of P(an) does not appear to fit an "all-out" pattern, with near zero values during the last portion of the event, as assumed in our previous model (De Koning JJ, de Groot G, and van Ingen Schenau GJ. J Biomech 25: 573-580, 1992). Skating position changed in ways different from those assumed in our previous model. In addition to allowing improved predictions, the results demonstrate the importance of observations in unique subjects to the process of model construction.
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