Critical speed estimated by statistically appropriate fitting procedures.

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Serval ID
serval:BIB_5C12A63351F6
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Critical speed estimated by statistically appropriate fitting procedures.
Journal
European journal of applied physiology
Author(s)
Patoz A., Spicher R., Pedrani N., Malatesta D., Borrani F.
ISSN
1439-6327 (Electronic)
ISSN-L
1439-6319
Publication state
Published
Issued date
07/2021
Peer-reviewed
Oui
Volume
121
Number
7
Pages
2027-2038
Language
english
Notes
Publication types: Journal Article
Publication Status: ppublish
Abstract
Intensity domains are recommended when prescribing exercise. The distinction between heavy and severe domains is made by the critical speed (CS), therefore requiring a mathematically accurate estimation of CS. The different model variants (distance versus time, running speed versus time, time versus running speed, and distance versus running speed) are mathematically equivalent. Nevertheless, error minimization along the correct axis is important to estimate CS and the distance that can be run above CS (d'). We hypothesized that comparing statistically appropriate fitting procedures, which minimize the error along the axis corresponding to the properly identified dependent variable, should provide similar estimations of CS and d' but that different estimations should be obtained when comparing statistically appropriate and inappropriate fitting procedure.
Sixteen male runners performed a maximal incremental aerobic test and four exhaustive runs at 90, 100, 110, and 120% of their peak speed on a treadmill. Several fitting procedures (a combination of a two-parameter model variant and regression analysis: weighted least square) were used to estimate CS and d'.
Systematic biases (P < 0.001) were observed between each pair of fitting procedures for CS and d', even when comparing two statistically appropriate fitting procedures, though negligible, thus corroborating the hypothesis.
The differences suggest that a statistically appropriate fitting procedure should be chosen beforehand by the researcher. This is also important for coaches that need to prescribe training sessions to their athletes based on exercise intensity, and their choice should be maintained over the running seasons.
Keywords
Acceleration, Adult, Exercise Test/methods, Humans, Male, Models, Statistical, Oxygen Consumption/physiology, Physical Endurance/physiology, Respiratory Mechanics/physiology, Running/physiology, Curve fitting, Exercise prescription, Hyperbolic model, Intensity domains, Linear model, Running
Pubmed
Web of science
Open Access
Yes
Funding(s)
University of Lausanne
Create date
03/04/2021 18:42
Last modification date
21/11/2022 8:24
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