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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/25/8/1119 |
| _version_ | 1797584862964613120 |
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| author | Florent Palacin Luc Poinsard Jean Renaud Pycke Véronique Billat |
| author_facet | Florent Palacin Luc Poinsard Jean Renaud Pycke Véronique Billat |
| author_sort | Florent Palacin |
| collection | DOAJ |
| 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 (<i>p</i> < 0.001). These findings suggest that integrating stride length’s Entropy feedback into new cardioGPS watches could improve marathon runners’ performance. |
| first_indexed | 2024-03-10T23:58:45Z |
| format | Article |
| id | doaj.art-e128eaa117834668b04a580cfa048dce |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-10T23:58:45Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-e128eaa117834668b04a580cfa048dce2023-11-19T00:58:50ZengMDPI AGEntropy1099-43002023-07-01258111910.3390/e25081119A Pilot Study Using Entropy for Optimizing Self-Pacing during a MarathonFlorent Palacin0Luc Poinsard1Jean Renaud Pycke2Véronique Billat3Laboratory of Neurophysiology and Movement Biomechanics, Université Libre de Bruxelles Neuroscience Institut, 1070 Bruxelles, BelgiumLaboratory of Neurophysiology and Movement Biomechanics, Université Libre de Bruxelles Neuroscience Institut, 1070 Bruxelles, BelgiumUMR8071-CNRS-Laboratoire de Mathématiques et Modélisation d’Evry, Université Paris-Saclay, Univ Evry, 91000 Evry-Courcouronnes, FranceEA 4526-Laboratoire IBISC Paris-Saclay, Univ Evry, 91000 Evry-Courcouronnes, FranceA 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 (<i>p</i> < 0.001). These findings suggest that integrating stride length’s Entropy feedback into new cardioGPS watches could improve marathon runners’ performance.https://www.mdpi.com/1099-4300/25/8/1119marathon runninghitting the wallShannon entropystride lengthperformance |
| spellingShingle | Florent Palacin Luc Poinsard Jean Renaud Pycke Véronique Billat A Pilot Study Using Entropy for Optimizing Self-Pacing during a Marathon Entropy marathon running hitting the wall Shannon entropy stride length performance |
| 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 | marathon running hitting the wall Shannon entropy stride length performance |
| url | https://www.mdpi.com/1099-4300/25/8/1119 |
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