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A Pilot Study Using Entropy for Optimizing Self-Pacing during a Marathon
A new group of marathon participants with minimal prior experience encounters the phenomenon known as “hitting the wall,” characterized by a notable decline in velocity accompanied by the heightened perception of fatigue (rate of perceived exertion, RPE). Previous research has suggested that success...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10453470/ https://www.ncbi.nlm.nih.gov/pubmed/37628149 http://dx.doi.org/10.3390/e25081119 |
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author | Palacin, Florent Poinsard, Luc Pycke, Jean Renaud Billat, Véronique |
author_facet | Palacin, Florent Poinsard, Luc Pycke, Jean Renaud Billat, Véronique |
author_sort | Palacin, Florent |
collection | PubMed |
description | A new group of marathon participants with minimal prior experience encounters the phenomenon known as “hitting the wall,” characterized by a notable decline in velocity accompanied by the heightened perception of fatigue (rate of perceived exertion, RPE). Previous research has suggested that successfully completing a marathon requires self-pacing according to RPE rather than attempting to maintain a constant speed or heart rate. However, it remains unclear how runners can self-pace their races based on the signals received from their physiological and mechanical running parameters. This study aims to investigate the relationship between the amount of information conveyed in a message or signal, RPE, and performance. It is hypothesized that a reduction in physiological or mechanical information (quantified by Shannon Entropy) affects performance. The entropy of heart rate, speed, and stride length was calculated for each kilometer of the race. The results showed that stride length had the highest entropy among the variables, and a reduction in its entropy to less than 50% of its maximum value (H = 3.3) was strongly associated with the distance (between 22 and 40) at which participants reported “hard exertion” (as indicated by an RPE of 15) and their performance (p < 0.001). These findings suggest that integrating stride length’s Entropy feedback into new cardioGPS watches could improve marathon runners’ performance. |
format | Online Article Text |
id | pubmed-10453470 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-104534702023-08-26 A Pilot Study Using Entropy for Optimizing Self-Pacing during a Marathon Palacin, Florent Poinsard, Luc Pycke, Jean Renaud Billat, Véronique Entropy (Basel) Article A new group of marathon participants with minimal prior experience encounters the phenomenon known as “hitting the wall,” characterized by a notable decline in velocity accompanied by the heightened perception of fatigue (rate of perceived exertion, RPE). Previous research has suggested that successfully completing a marathon requires self-pacing according to RPE rather than attempting to maintain a constant speed or heart rate. However, it remains unclear how runners can self-pace their races based on the signals received from their physiological and mechanical running parameters. This study aims to investigate the relationship between the amount of information conveyed in a message or signal, RPE, and performance. It is hypothesized that a reduction in physiological or mechanical information (quantified by Shannon Entropy) affects performance. The entropy of heart rate, speed, and stride length was calculated for each kilometer of the race. The results showed that stride length had the highest entropy among the variables, and a reduction in its entropy to less than 50% of its maximum value (H = 3.3) was strongly associated with the distance (between 22 and 40) at which participants reported “hard exertion” (as indicated by an RPE of 15) and their performance (p < 0.001). These findings suggest that integrating stride length’s Entropy feedback into new cardioGPS watches could improve marathon runners’ performance. MDPI 2023-07-26 /pmc/articles/PMC10453470/ /pubmed/37628149 http://dx.doi.org/10.3390/e25081119 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Palacin, Florent Poinsard, Luc Pycke, Jean Renaud Billat, Véronique A Pilot Study Using Entropy for Optimizing Self-Pacing during a Marathon |
title | A Pilot Study Using Entropy for Optimizing Self-Pacing during a Marathon |
title_full | A Pilot Study Using Entropy for Optimizing Self-Pacing during a Marathon |
title_fullStr | A Pilot Study Using Entropy for Optimizing Self-Pacing during a Marathon |
title_full_unstemmed | A Pilot Study Using Entropy for Optimizing Self-Pacing during a Marathon |
title_short | A Pilot Study Using Entropy for Optimizing Self-Pacing during a Marathon |
title_sort | pilot study using entropy for optimizing self-pacing during a marathon |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10453470/ https://www.ncbi.nlm.nih.gov/pubmed/37628149 http://dx.doi.org/10.3390/e25081119 |
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