Literature DB >> 24566607

Differences among estimates of critical power and anaerobic work capacity derived from five mathematical models and the three-minute all-out test.

Haley C Bergstrom1, Terry J Housh, Jorge M Zuniga, Daniel A Traylor, Robert W Lewis, Clayton L Camic, Richard J Schmidt, Glen O Johnson.   

Abstract

Estimates of critical power (CP) and anaerobic work capacity (AWC) from the power output vs. time relationship have been derived from various mathematical models. The purpose of this study was to examine estimates of CP and AWC from the multiple work bout, 2- and 3-parameter models, and those from the 3-minute all-out CP (CP3min) test. Nine college-aged subjects performed a maximal incremental test to determine the peak oxygen consumption rate and the gas exchange threshold. On separate days, each subject completed 4 randomly ordered constant power output rides to exhaustion to estimate CP and AWC from 5 regression models (2 linear, 2 nonlinear, and 1 exponential). During the final visit, CP and AWC were estimated from the CP3min test. The nonlinear 3-parameter (Nonlinear-3) model produced the lowest estimate of CP. The exponential (EXP) model and the CP3min test were not statistically different and produced the highest estimates of CP. Critical power estimated from the Nonlinear-3 model was 14% less than those from the EXP model and the CP3min test and 4-6% less than those from the linear models. Furthermore, the Nonlinear-3 and nonlinear 2-parameter (Nonlinear-2) models produced significantly greater estimates of AWC than did the linear models and CP3min. The current findings suggested that the Nonlinear-3 model may provide estimates of CP and AWC that more accurately reflect the asymptote of the power output vs. time relationship, the demarcation of the heavy and severe exercise intensity domains, and anaerobic capabilities than will the linear models and CP3min test.

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Year:  2014        PMID: 24566607     DOI: 10.1519/JSC.0b013e31829b576d

Source DB:  PubMed          Journal:  J Strength Cond Res        ISSN: 1064-8011            Impact factor:   3.775


  13 in total

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Authors:  Leonardo H D Messias; Homero G Ferrari; Ivan G M Reis; Pedro P M Scariot; Fúlvia B Manchado-Gobatto
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3.  A 'ramp-sprint' protocol to characterise indices of aerobic function and exercise intensity domains in a single laboratory test.

Authors:  Scott R Murgatroyd; Lindsey A Wylde; Daniel T Cannon; Susan A Ward; Harry B Rossiter
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4.  Experimental validation of the 3-parameter critical power model in cycling.

Authors:  Giovanni Vinetti; Anna Taboni; Paolo Bruseghini; Stefano Camelio; Matteo D'Elia; Nazzareno Fagoni; Christian Moia; Guido Ferretti
Journal:  Eur J Appl Physiol       Date:  2019-01-29       Impact factor: 3.078

5.  The impact of elevated body core temperature on critical power as determined by a 3-min all-out test.

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Review 6.  Determination of Critical Power Using Different Possible Approaches among Endurance Athletes: A Review.

Authors:  Lucie Lipková; Michal Kumstát; Ivan Struhár
Journal:  Int J Environ Res Public Health       Date:  2022-06-21       Impact factor: 4.614

Review 7.  A critical review of critical power.

Authors:  Raffy Dotan
Journal:  Eur J Appl Physiol       Date:  2022-03-18       Impact factor: 3.346

8.  Modelling of Running Performances: Comparisons of Power-Law, Hyperbolic, Logarithmic, and Exponential Models in Elite Endurance Runners.

Authors:  H Vandewalle
Journal:  Biomed Res Int       Date:  2018-10-03       Impact factor: 3.411

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Authors:  Gerald T Mangine; Matthew T Stratton; Christian G Almeda; Michael D Roberts; Tiffany A Esmat; Trisha A VanDusseldorp; Yuri Feito
Journal:  PLoS One       Date:  2020-04-07       Impact factor: 3.240

10.  Examination of Resistance Settings Based on Body Weight for the 3-Minute All-Out Critical Power Test.

Authors:  Marlene J Schulte; Jody L Clasey; Bradley S Fleenor; Haley C Bergstrom
Journal:  Int J Exerc Sci       Date:  2018-01-01
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