Literature DB >> 17645369

Distribution of power output during cycling: impact and mechanisms.

Greg Atkinson1, Oliver Peacock, Alan St Clair Gibson, Ross Tucker.   

Abstract

We aim to summarise the impact and mechanisms of work-rate pacing during individual cycling time trials (TTs). Unlike time-to-exhaustion tests, a TT provides an externally valid model for examining how an initial work rate is chosen and maintained by an athlete during self-selected exercise. The selection and distribution of work rate is one of many factors that influence cycling speed. Mathematical models are available to predict the impact of factors such as gradient and wind velocity on cycling speed, but only a few researchers have examined the inter-relationships between these factors and work-rate distribution within a TT. When environmental conditions are relatively stable (e.g. in a velodrome) and the TT is >10 minutes, then an even distribution of work rate is optimal. For a shorter TT (< or = 10 minutes), work rate should be increased during the starting effort because this proportion of total race time is significant. For a very short TT (< or = 2 minutes), the starting effort should be maximal, since the time saved during the starting phase is predicted to outweigh any time lost during the final metres because of fatigue. A similar 'time saving' rationale underpins the advice that work rate should vary in parallel with any changes in gradient or wind speed during a road TT. Increasing work rate in headwind and uphill sections, and vice versa, decreases the variability in speed and, therefore, the total race time. It seems that even experienced cyclists naturally select a supraoptimal work rate at the start of a longer TT. Whether such a start can be 'blunted' through coaching or the monitoring of psychophysiological variables is unknown. Similarly, the extent to which cyclists can vary and monitor work rate during a TT is unclear. There is evidence that sub-elite cyclists can vary work rate by +/-5% the average for a TT lasting 25-60 minutes, but such variability might be difficult with high-performance cyclists whose average work rate during a TT is already extremely high (>350 watts). During a TT, pacing strategy is regulated in a complex anticipatory system that monitors afferent feedback from various physiological systems, and then regulates the work rate so that potentially limiting changes do not occur before the endpoint of exercise is reached. It is critical that the endpoint of exercise is known by the cyclist so that adjustments to exercise work rate can be made within the context of an estimated finish time. Pacing strategies are thus the consequence of complex regulation and serve a dual role: they are both the result of homeostatic regulation by the brain, as well as being the means by which such regulation is achieved. The pacing strategy 'algorithm' is sited in the brain and would need afferent input from interoceptors, such as heart rate and respiratory rate, as well as exteroceptors providing information on local environmental conditions. Such inputs have been shown to induce activity in the thalamus, hypothalamus and the parietal somatosensory cortex. Knowledge of time, modulated by the cerebellum, basal ganglia and primary somatosensory cortex, would also input to the pacing algorithm as would information stored in memory about previous similar exercise bouts. How all this information is assimilated by the different regions of the brain is not known at present.

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Mesh:

Year:  2007        PMID: 17645369     DOI: 10.2165/00007256-200737080-00001

Source DB:  PubMed          Journal:  Sports Med        ISSN: 0112-1642            Impact factor:   11.136


  104 in total

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Review 7.  The slow component of oxygen uptake kinetics in humans.

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8.  Effect of pacing strategy on cycle time trial performance.

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Journal:  Med Sci Sports Exerc       Date:  1993-03       Impact factor: 5.411

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Authors:  J E Peltonen; J Rantamäki; S P Niittymäki; K Sweins; J T Viitasalo; H K Rusko
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  18 in total

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Authors:  Christophe Hausswirth; Jeanick Brisswalter
Journal:  Sports Med       Date:  2008       Impact factor: 11.136

3.  The effect of an even-pacing strategy on exercise tolerance in well-trained cyclists.

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4.  Influence of accurate and inaccurate 'split-time' feedback upon 10-mile time trial cycling performance.

Authors:  Mathew G Wilson; Andy M Lane; Chris J Beedie; Abdulaziz Farooq
Journal:  Eur J Appl Physiol       Date:  2011-05-01       Impact factor: 3.078

5.  Is it time to retire the A.V. Hill Model?: A rebuttal to the article by Professor Roy Shephard.

Authors:  Timothy D Noakes
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Review 6.  Strategies of dietary carbohydrate manipulation and their effects on performance in cycling time trials.

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8.  High energy deficit in an ultraendurance athlete in a 24-hour ultracycling race.

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9.  Effect of performance level on pacing strategy during a 10-km running race.

Authors:  Adriano E Lima-Silva; Romulo C M Bertuzzi; Flavio O Pires; Ronaldo V Barros; João F Gagliardi; John Hammond; Maria A Kiss; David J Bishop
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Review 10.  Crawling to the finish line: why do endurance runners collapse? Implications for understanding of mechanisms underlying pacing and fatigue.

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