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Training zones through muscle oxygen saturation during a graded exercise test in cyclists and triathletes

Use of muscle oxygen saturation (SmO(2)) has been validated as a performance factor during incremental exercise with portable near-infrared stereoscopy (NIRS) technology. However, there is little knowledge about the use of SmO(2) to identify training zones. The objective of this study was to evaluat...

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Autores principales: Vasquez Bonilla, Aldo A., González-Custodio, Adrián, Timón, Rafael, Camacho-Cardenosa, Alba, Camacho-Cardenosa, Marta, Olcina, Guillermo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Institute of Sport in Warsaw 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10108753/
https://www.ncbi.nlm.nih.gov/pubmed/37077776
http://dx.doi.org/10.5114/biolsport.2023.114288
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author Vasquez Bonilla, Aldo A.
González-Custodio, Adrián
Timón, Rafael
Camacho-Cardenosa, Alba
Camacho-Cardenosa, Marta
Olcina, Guillermo
author_facet Vasquez Bonilla, Aldo A.
González-Custodio, Adrián
Timón, Rafael
Camacho-Cardenosa, Alba
Camacho-Cardenosa, Marta
Olcina, Guillermo
author_sort Vasquez Bonilla, Aldo A.
collection PubMed
description Use of muscle oxygen saturation (SmO(2)) has been validated as a performance factor during incremental exercise with portable near-infrared stereoscopy (NIRS) technology. However, there is little knowledge about the use of SmO(2) to identify training zones. The objective of this study was to evaluate the metabolic zones by SmO(2): maximum lipid oxidation zone (Fatmax), ventilatory thresholds (VT1 and VT2) and maximum aerobic power (MAP) during a graded exercise test (GXT). Forty trained cyclists and triathletes performed a GXT. Output power (W), heart rate (HR), oxygen consumption (VO(2)), energy expenditure (kcal/min) and SmO(2) were measured. Data were analysed using the ANOVA test, ROC curves and multiple linear regressions. Significance was established at p ≤ 0.05. SmO(2) decreases were observed from baseline (LB) to Fatmax (Δ = -16% p < 0.05), Fatmax to VT1 (Δ = -16% p < 0.05) and VT1 to VT2 (Δ = -45% p < 0.01). Furthermore, SmO(2) together with weight, HR and output power have the ability to predict VO(2) and energy expenditure by 89% and 90%, respectively. We conclude that VO(2) and energy expenditure values can be approximated using SmO(2) together with other physiological parameters and SmO(2) measurements can be a complementary parameter to discriminate aerobic workload and anaerobic workload in athletes.
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spelling pubmed-101087532023-04-18 Training zones through muscle oxygen saturation during a graded exercise test in cyclists and triathletes Vasquez Bonilla, Aldo A. González-Custodio, Adrián Timón, Rafael Camacho-Cardenosa, Alba Camacho-Cardenosa, Marta Olcina, Guillermo Biol Sport Original Paper Use of muscle oxygen saturation (SmO(2)) has been validated as a performance factor during incremental exercise with portable near-infrared stereoscopy (NIRS) technology. However, there is little knowledge about the use of SmO(2) to identify training zones. The objective of this study was to evaluate the metabolic zones by SmO(2): maximum lipid oxidation zone (Fatmax), ventilatory thresholds (VT1 and VT2) and maximum aerobic power (MAP) during a graded exercise test (GXT). Forty trained cyclists and triathletes performed a GXT. Output power (W), heart rate (HR), oxygen consumption (VO(2)), energy expenditure (kcal/min) and SmO(2) were measured. Data were analysed using the ANOVA test, ROC curves and multiple linear regressions. Significance was established at p ≤ 0.05. SmO(2) decreases were observed from baseline (LB) to Fatmax (Δ = -16% p < 0.05), Fatmax to VT1 (Δ = -16% p < 0.05) and VT1 to VT2 (Δ = -45% p < 0.01). Furthermore, SmO(2) together with weight, HR and output power have the ability to predict VO(2) and energy expenditure by 89% and 90%, respectively. We conclude that VO(2) and energy expenditure values can be approximated using SmO(2) together with other physiological parameters and SmO(2) measurements can be a complementary parameter to discriminate aerobic workload and anaerobic workload in athletes. Institute of Sport in Warsaw 2022-06-01 2023-04 /pmc/articles/PMC10108753/ /pubmed/37077776 http://dx.doi.org/10.5114/biolsport.2023.114288 Text en Copyright © Biology of Sport 2023 https://creativecommons.org/licenses/by-sa/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Share Alike 4.0 License, allowing third parties to copy and redistribute the material in any medium or format and remix, transform, and build upon the material for any purpose, even commercially, provided the original work is properly cited and states its license.
spellingShingle Original Paper
Vasquez Bonilla, Aldo A.
González-Custodio, Adrián
Timón, Rafael
Camacho-Cardenosa, Alba
Camacho-Cardenosa, Marta
Olcina, Guillermo
Training zones through muscle oxygen saturation during a graded exercise test in cyclists and triathletes
title Training zones through muscle oxygen saturation during a graded exercise test in cyclists and triathletes
title_full Training zones through muscle oxygen saturation during a graded exercise test in cyclists and triathletes
title_fullStr Training zones through muscle oxygen saturation during a graded exercise test in cyclists and triathletes
title_full_unstemmed Training zones through muscle oxygen saturation during a graded exercise test in cyclists and triathletes
title_short Training zones through muscle oxygen saturation during a graded exercise test in cyclists and triathletes
title_sort training zones through muscle oxygen saturation during a graded exercise test in cyclists and triathletes
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10108753/
https://www.ncbi.nlm.nih.gov/pubmed/37077776
http://dx.doi.org/10.5114/biolsport.2023.114288
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