# Effect of Mathematical Modeling and Fitting Procedures on the Assessment of Critical Speed and Its Relationship With Aerobic Fitness Parameters.

## Détails

Télécharger: fphys-12-613066.pdf (448.15 [Ko])

Etat: Public

Version: Final published version

Licence: Non spécifiée

Etat: Public

Version: Final published version

Licence: Non spécifiée

ID Serval

serval:BIB_BF88AC7E0221

Type

**Article**: article d'un périodique ou d'un magazine.

Collection

Publications

Institution

Titre

Effect of Mathematical Modeling and Fitting Procedures on the Assessment of Critical Speed and Its Relationship With Aerobic Fitness Parameters.

Périodique

Frontiers in physiology

ISSN

1664-042X (Print)

ISSN-L

1664-042X

Statut éditorial

Publié

Date de publication

2021

Peer-reviewed

Oui

Volume

12

Pages

613066

Langue

anglais

Notes

Publication types: Journal Article

Publication Status: epublish

Publication Status: epublish

Résumé

An accurate estimation of critical speed (CS) is important to accurately define the boundary between heavy and severe intensity domains when prescribing exercise. Hence, our aim was to compare CS estimates obtained by statistically appropriate fitting procedures, i.e., regression analyses that correctly consider the dependent variables of the underlying models. A second aim was to determine the correlations between estimated CS and aerobic fitness parameters, i.e., ventilatory threshold, respiratory compensation point, and maximal rate of oxygen uptake. Sixteen male runners performed a maximal incremental aerobic test and four exhaustive runs at 90, 100, 110, and 120% of the peak speed of the incremental test on a treadmill. Then, two mathematically equivalent formulations (time as function of running speed and distance as function of running speed) of three different mathematical models (two-parameter, three-parameter, and three-parameter exponential) were employed to estimate CS, the distance that can be run above CS (d'), and if applicable, the maximal instantaneous running speed (s <sub>max</sub> ). A significant effect of the mathematical model was observed when estimating CS, d', and s <sub>max</sub> (P < 0.001), but there was no effect of the fitting procedure (P > 0.77). The three-parameter model had the best fit quality (smallest Akaike information criterion) of the CS estimates but the highest 90% confidence intervals and combined standard error of estimates (%SEE). The 90% CI and %SEE were similar when comparing the two fitting procedures for a given model. High and very high correlations were obtained between CS and aerobic fitness parameters for the three different models (r ≥ 0.77) as well as reasonably small SEE (SEE ≤ 6.8%). However, our results showed no further support for selecting the best mathematical model to estimate critical speed. Nonetheless, we suggest coaches choosing a mathematical model beforehand to define intensity domains and maintaining it over the running seasons.

Mots-clé

Physiology (medical), Physiology, curve fitting, exercise prescription, exponential model, hyperbolic model, linear model, running

Pubmed

Web of science

Open Access

Oui

Création de la notice

31/05/2021 8:19

Dernière modification de la notice

21/11/2022 9:27