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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Institute of Sport in Warsaw
2022
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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. |
format | Online Article Text |
id | pubmed-10108753 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Institute of Sport in Warsaw |
record_format | MEDLINE/PubMed |
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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