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Monitoring Fatigue During Intermittent Exercise With Accelerometer-Derived Metrics
The aim of this study was to assess the sensitivity of accelerometer-derived metrics for monitoring fatigue during an intermittent exercise protocol. Fifteen university students were enrolled in the study (age 20 ± 1 years). A submaximal intermitted recovery test (Sub-IRT) with a duration of 6 min a...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6606691/ https://www.ncbi.nlm.nih.gov/pubmed/31293447 http://dx.doi.org/10.3389/fphys.2019.00780 |
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author | Beato, Marco De Keijzer, Kevin L. Carty, Benjamin Connor, Mark |
author_facet | Beato, Marco De Keijzer, Kevin L. Carty, Benjamin Connor, Mark |
author_sort | Beato, Marco |
collection | PubMed |
description | The aim of this study was to assess the sensitivity of accelerometer-derived metrics for monitoring fatigue during an intermittent exercise protocol. Fifteen university students were enrolled in the study (age 20 ± 1 years). A submaximal intermitted recovery test (Sub-IRT) with a duration of 6 min and 30 s (drill 1) was performed. In order to increase the participants’ fatigue, after that, a repeated sprint protocol (1×6 maximal 20 m sprints) was performed. Following that, participants repeated the Sub-IRT (drill 2) to evaluate the external and internal training load (TL) variations related to fatigue. Apex 10 Hz global navigation satellite system (GNSS) units were used to collect the variables total distance (TD), high metabolic distance (HMD), relative velocity (RV), average metabolic power (MP), heart rate maximal (HRmax) and mean (HRmean), muscular (RPEmus) and respiratory rating of perceived exertion (RPEres), dynamic stress load (DSL), and fatigue index (FI). A Bayesian statistical approach was used. A likelihood difference (between drill 1 and drill 2) was found for the following parameters: TD (BF(10) = 0.33, moderate per H(0)), HMD (BF(10) = 1.3, anecdotal), RV (BF(10) = 0.29, moderate per H(0)), MP (BF(10) = 1.3, anecdotal), accelerations (BF(10) = 1.6, anecdotal ), FI (BF(10) = 4.7, moderate), HRmax (BF(10) = 2.2, anecdotal), HRmean (BF(10) = 4.3, moderate), RPEmus (BF(10) = 11.6, strong), RPEres (BF(10) = 3.1, moderate), DSL (BF(10) = 5.7, moderate), and DSL•m(−1) (BF(10) = 4.3, moderate). In conclusion, this study reports that DSL, DSL•m(−1), and FI can be valid metrics to monitor fatigue related to movement strategy during a standardized submaximal intermittent exercise protocol. |
format | Online Article Text |
id | pubmed-6606691 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-66066912019-07-10 Monitoring Fatigue During Intermittent Exercise With Accelerometer-Derived Metrics Beato, Marco De Keijzer, Kevin L. Carty, Benjamin Connor, Mark Front Physiol Physiology The aim of this study was to assess the sensitivity of accelerometer-derived metrics for monitoring fatigue during an intermittent exercise protocol. Fifteen university students were enrolled in the study (age 20 ± 1 years). A submaximal intermitted recovery test (Sub-IRT) with a duration of 6 min and 30 s (drill 1) was performed. In order to increase the participants’ fatigue, after that, a repeated sprint protocol (1×6 maximal 20 m sprints) was performed. Following that, participants repeated the Sub-IRT (drill 2) to evaluate the external and internal training load (TL) variations related to fatigue. Apex 10 Hz global navigation satellite system (GNSS) units were used to collect the variables total distance (TD), high metabolic distance (HMD), relative velocity (RV), average metabolic power (MP), heart rate maximal (HRmax) and mean (HRmean), muscular (RPEmus) and respiratory rating of perceived exertion (RPEres), dynamic stress load (DSL), and fatigue index (FI). A Bayesian statistical approach was used. A likelihood difference (between drill 1 and drill 2) was found for the following parameters: TD (BF(10) = 0.33, moderate per H(0)), HMD (BF(10) = 1.3, anecdotal), RV (BF(10) = 0.29, moderate per H(0)), MP (BF(10) = 1.3, anecdotal), accelerations (BF(10) = 1.6, anecdotal ), FI (BF(10) = 4.7, moderate), HRmax (BF(10) = 2.2, anecdotal), HRmean (BF(10) = 4.3, moderate), RPEmus (BF(10) = 11.6, strong), RPEres (BF(10) = 3.1, moderate), DSL (BF(10) = 5.7, moderate), and DSL•m(−1) (BF(10) = 4.3, moderate). In conclusion, this study reports that DSL, DSL•m(−1), and FI can be valid metrics to monitor fatigue related to movement strategy during a standardized submaximal intermittent exercise protocol. Frontiers Media S.A. 2019-06-26 /pmc/articles/PMC6606691/ /pubmed/31293447 http://dx.doi.org/10.3389/fphys.2019.00780 Text en Copyright © 2019 Beato, De Keijzer, Carty and Connor. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Physiology Beato, Marco De Keijzer, Kevin L. Carty, Benjamin Connor, Mark Monitoring Fatigue During Intermittent Exercise With Accelerometer-Derived Metrics |
title | Monitoring Fatigue During Intermittent Exercise With Accelerometer-Derived Metrics |
title_full | Monitoring Fatigue During Intermittent Exercise With Accelerometer-Derived Metrics |
title_fullStr | Monitoring Fatigue During Intermittent Exercise With Accelerometer-Derived Metrics |
title_full_unstemmed | Monitoring Fatigue During Intermittent Exercise With Accelerometer-Derived Metrics |
title_short | Monitoring Fatigue During Intermittent Exercise With Accelerometer-Derived Metrics |
title_sort | monitoring fatigue during intermittent exercise with accelerometer-derived metrics |
topic | Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6606691/ https://www.ncbi.nlm.nih.gov/pubmed/31293447 http://dx.doi.org/10.3389/fphys.2019.00780 |
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