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Mechanical Work and Long-Distance Performance Prediction: the Influence of Allometric Scaling
The purpose of this study was to examine the effect of allometric scaling on the relationship between mechanical work and long-distance running performance in recreational runners. Fourteen recreational long-distance runners (male, mean ± SD - age: 29 ± 7 years; body mass: 70.0 ± 10.2 kg; body heigh...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Akademia Wychowania Fizycznego w Katowicach
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3827753/ https://www.ncbi.nlm.nih.gov/pubmed/24235986 http://dx.doi.org/10.2478/hukin-2013-0047 |
Sumario: | The purpose of this study was to examine the effect of allometric scaling on the relationship between mechanical work and long-distance running performance in recreational runners. Fourteen recreational long-distance runners (male, mean ± SD - age: 29 ± 7 years; body mass: 70.0 ± 10.2 kg; body height: 1.71 ± 0.07 m; maximal oxygen uptake: VO(2max) 52.0 ± 4.9 ml·kg(−1)·min(−1)) performed two tests: a continuous incremental test to volitional exhaustion in order to determine VO(2max), and a 6-minute running submaximal test at 3.1 m·s(−1), during which segments in the sagittal plane were recorded using a digital camera and the internal (W(int)), external (W(ext)) and total (W(tot)) mechanic work, in J·kg(−1)·m(−1), was subsequently calculated. The results indicated a significant correlation between mechanical work and performance, however, the strongest correlations were observed when allometric exponents were used (respectively for W(int), W(ext) and W(tot); non allometric vs. allometric scaling defined by literature (0.75) or determined mathematically (0.49): r = 0.38 vs. r = 0.44 and r = 0.50; r = 0.80 vs. r = 0.83 and r = 0.82; r = 0.70 vs. r = 0.77 and r = 0.78). These results indicate that mechanical work could be used as a predictor of recreational long-distance performance and an allometric model may improve this prediction. |
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