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Full course macro-kinematic analysis of a 10 km classical cross-country skiing competition

In this study micro-sensors were employed to analyse macro-kinematic parameters during a classical cross-country skiing competition (10 km, 2-lap). Data were collected from eight male participants during the Australian championship competition wearing a single micro-sensor unit (MinimaxX™, S4) posit...

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Autores principales: Marsland, Finn, Mackintosh, Colin, Holmberg, Hans-Christer, Anson, Judith, Waddington, Gordon, Lyons, Keith, Chapman, Dale
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5538647/
https://www.ncbi.nlm.nih.gov/pubmed/28763504
http://dx.doi.org/10.1371/journal.pone.0182262
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author Marsland, Finn
Mackintosh, Colin
Holmberg, Hans-Christer
Anson, Judith
Waddington, Gordon
Lyons, Keith
Chapman, Dale
author_facet Marsland, Finn
Mackintosh, Colin
Holmberg, Hans-Christer
Anson, Judith
Waddington, Gordon
Lyons, Keith
Chapman, Dale
author_sort Marsland, Finn
collection PubMed
description In this study micro-sensors were employed to analyse macro-kinematic parameters during a classical cross-country skiing competition (10 km, 2-lap). Data were collected from eight male participants during the Australian championship competition wearing a single micro-sensor unit (MinimaxX™, S4) positioned on their upper back. Algorithms and visual classification were used to identify skiing sub-techniques and calculate velocities, cycle lengths (CL) and cycle rates (CR) over the entire course. Double poling (DP) was the predominant cyclical sub-technique utilised (43 ± 5% of total distance), followed by diagonal stride (DS, 16 ± 4%) and kick double poling (KDP, 5 ± 4%), with the non-propulsive Tuck technique accounting for 24 ± 4% of the course. Large within-athlete variances in CL and CR occurred, particularly for DS (CV% = 25 ± 2% and CV% = 15 ± 2%, respectively). For all sub-techniques the mean CR on both laps and for the slower and faster skiers were similar, while there was a trend for the mean velocities in all sub-techniques by the faster athletes to be higher. Overall velocity and mean DP-CL were significantly higher on Lap 1, with no significant change in KDP-CL or DS-CL between laps. Distinct individual velocity thresholds for transitions between sub-techniques were observed. Clearly, valuable insights into cross-country skiing performance can be gained through continuous macro-kinematic monitoring during competition.
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spelling pubmed-55386472017-08-07 Full course macro-kinematic analysis of a 10 km classical cross-country skiing competition Marsland, Finn Mackintosh, Colin Holmberg, Hans-Christer Anson, Judith Waddington, Gordon Lyons, Keith Chapman, Dale PLoS One Research Article In this study micro-sensors were employed to analyse macro-kinematic parameters during a classical cross-country skiing competition (10 km, 2-lap). Data were collected from eight male participants during the Australian championship competition wearing a single micro-sensor unit (MinimaxX™, S4) positioned on their upper back. Algorithms and visual classification were used to identify skiing sub-techniques and calculate velocities, cycle lengths (CL) and cycle rates (CR) over the entire course. Double poling (DP) was the predominant cyclical sub-technique utilised (43 ± 5% of total distance), followed by diagonal stride (DS, 16 ± 4%) and kick double poling (KDP, 5 ± 4%), with the non-propulsive Tuck technique accounting for 24 ± 4% of the course. Large within-athlete variances in CL and CR occurred, particularly for DS (CV% = 25 ± 2% and CV% = 15 ± 2%, respectively). For all sub-techniques the mean CR on both laps and for the slower and faster skiers were similar, while there was a trend for the mean velocities in all sub-techniques by the faster athletes to be higher. Overall velocity and mean DP-CL were significantly higher on Lap 1, with no significant change in KDP-CL or DS-CL between laps. Distinct individual velocity thresholds for transitions between sub-techniques were observed. Clearly, valuable insights into cross-country skiing performance can be gained through continuous macro-kinematic monitoring during competition. Public Library of Science 2017-08-01 /pmc/articles/PMC5538647/ /pubmed/28763504 http://dx.doi.org/10.1371/journal.pone.0182262 Text en © 2017 Marsland et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Marsland, Finn
Mackintosh, Colin
Holmberg, Hans-Christer
Anson, Judith
Waddington, Gordon
Lyons, Keith
Chapman, Dale
Full course macro-kinematic analysis of a 10 km classical cross-country skiing competition
title Full course macro-kinematic analysis of a 10 km classical cross-country skiing competition
title_full Full course macro-kinematic analysis of a 10 km classical cross-country skiing competition
title_fullStr Full course macro-kinematic analysis of a 10 km classical cross-country skiing competition
title_full_unstemmed Full course macro-kinematic analysis of a 10 km classical cross-country skiing competition
title_short Full course macro-kinematic analysis of a 10 km classical cross-country skiing competition
title_sort full course macro-kinematic analysis of a 10 km classical cross-country skiing competition
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5538647/
https://www.ncbi.nlm.nih.gov/pubmed/28763504
http://dx.doi.org/10.1371/journal.pone.0182262
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