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Using Statistical Parametric Mapping as a statistical method for more detailed insights in swimming: a systematic review
Swimming is a time-based sport and hence strongly dependent from velocity. Most studies about swimming refer to velocity as discrete variable, i.e., 0-D (no time dimension). However, it was argued that using swimming velocity as a continuous variable (1-D, with time dimension) with Statistical Param...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10339380/ https://www.ncbi.nlm.nih.gov/pubmed/37457037 http://dx.doi.org/10.3389/fphys.2023.1213151 |
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author | Morais, Jorge E. Barbosa, Tiago M. Gonjo, Tomohiro Marinho, Daniel A. |
author_facet | Morais, Jorge E. Barbosa, Tiago M. Gonjo, Tomohiro Marinho, Daniel A. |
author_sort | Morais, Jorge E. |
collection | PubMed |
description | Swimming is a time-based sport and hence strongly dependent from velocity. Most studies about swimming refer to velocity as discrete variable, i.e., 0-D (no time dimension). However, it was argued that using swimming velocity as a continuous variable (1-D, with time dimension) with Statistical Parametric Mapping (SPM) can bring deeper and detailed insights about swimming performance. Therefore, the aim of this study was to perform a systematic review about the current body of knowledge of using Statistical Parametric Mapping in a swimming context. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used to identify relevant articles. After screening, nine articles related to Statistical Parametric Mapping (SPM) analysis in swimming were retained for synthesis. Results showed that four articles (44.4%) aimed to understand the kinematics, isokinetic joint torque or electromyographic (EMG) pattern of the swimmer’s shoulder either on land or during front crawl trials. Two articles (22.2%) focused on understanding the swimming velocity while performing the breaststroke stroke. One article (11.1%) analyzed the swimmers’ propulsion at front-crawl stroke, another one (11.1%) compared swimming velocity during a complete stroke cycle in young swimmers of both sexes as a discrete variable and as a continuous variable. Also, one article (11.1%) analyzed the underwater undulatory velocity. In an EMG context, some findings verified in SPM are not possible to be discovered with traditional 0-D statistical methods. Studies about swimming velocity (breaststroke, freestyle, and underwater undulatory velocity) and propulsion (front-crawl) also highlighted the SPM advantages in comparison to traditional statistical methods. By using SPM, researchers were able to verify specifically where within the stroke cycle significant differences were found. Therefore, coaches can get more detailed information to design specific training drills to overcome hypothetical handicaps. |
format | Online Article Text |
id | pubmed-10339380 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-103393802023-07-14 Using Statistical Parametric Mapping as a statistical method for more detailed insights in swimming: a systematic review Morais, Jorge E. Barbosa, Tiago M. Gonjo, Tomohiro Marinho, Daniel A. Front Physiol Physiology Swimming is a time-based sport and hence strongly dependent from velocity. Most studies about swimming refer to velocity as discrete variable, i.e., 0-D (no time dimension). However, it was argued that using swimming velocity as a continuous variable (1-D, with time dimension) with Statistical Parametric Mapping (SPM) can bring deeper and detailed insights about swimming performance. Therefore, the aim of this study was to perform a systematic review about the current body of knowledge of using Statistical Parametric Mapping in a swimming context. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used to identify relevant articles. After screening, nine articles related to Statistical Parametric Mapping (SPM) analysis in swimming were retained for synthesis. Results showed that four articles (44.4%) aimed to understand the kinematics, isokinetic joint torque or electromyographic (EMG) pattern of the swimmer’s shoulder either on land or during front crawl trials. Two articles (22.2%) focused on understanding the swimming velocity while performing the breaststroke stroke. One article (11.1%) analyzed the swimmers’ propulsion at front-crawl stroke, another one (11.1%) compared swimming velocity during a complete stroke cycle in young swimmers of both sexes as a discrete variable and as a continuous variable. Also, one article (11.1%) analyzed the underwater undulatory velocity. In an EMG context, some findings verified in SPM are not possible to be discovered with traditional 0-D statistical methods. Studies about swimming velocity (breaststroke, freestyle, and underwater undulatory velocity) and propulsion (front-crawl) also highlighted the SPM advantages in comparison to traditional statistical methods. By using SPM, researchers were able to verify specifically where within the stroke cycle significant differences were found. Therefore, coaches can get more detailed information to design specific training drills to overcome hypothetical handicaps. Frontiers Media S.A. 2023-06-29 /pmc/articles/PMC10339380/ /pubmed/37457037 http://dx.doi.org/10.3389/fphys.2023.1213151 Text en Copyright © 2023 Morais, Barbosa, Gonjo and Marinho. https://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 Morais, Jorge E. Barbosa, Tiago M. Gonjo, Tomohiro Marinho, Daniel A. Using Statistical Parametric Mapping as a statistical method for more detailed insights in swimming: a systematic review |
title | Using Statistical Parametric Mapping as a statistical method for more detailed insights in swimming: a systematic review |
title_full | Using Statistical Parametric Mapping as a statistical method for more detailed insights in swimming: a systematic review |
title_fullStr | Using Statistical Parametric Mapping as a statistical method for more detailed insights in swimming: a systematic review |
title_full_unstemmed | Using Statistical Parametric Mapping as a statistical method for more detailed insights in swimming: a systematic review |
title_short | Using Statistical Parametric Mapping as a statistical method for more detailed insights in swimming: a systematic review |
title_sort | using statistical parametric mapping as a statistical method for more detailed insights in swimming: a systematic review |
topic | Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10339380/ https://www.ncbi.nlm.nih.gov/pubmed/37457037 http://dx.doi.org/10.3389/fphys.2023.1213151 |
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