Literature DB >> 7964412

Mechanical determinants of the minimum energy cost of gradient running in humans.

A E Minetti1, L P Ardigò, F Saibene.   

Abstract

The metabolic cost and the mechanical work of running at different speeds and gradients were measured on five human subjects. The mechanical work was partitioned into the internal work (Wint) due to the speed changes of body segments with respect to the body centre of mass and the external work (Wext) due to the position and speed changes of the body centre of mass in the environment. Wext was further divided into a positive part (W+ext) and a negative part (W-ext), associated with the energy increases and decreases, respectively, over the stride period. For all constant speeds, the most economical gradient was -10.6 +/-0.5% (S.D., N = 5) with a metabolic cost of 146.8 +/- 3.8 ml O2 kg-1 km-1. At each gradient, there was a unique W+ext/W-ext ratio (which was 1 in level running), irrespective of speed, with a tendency for W-ext and W+ext to disappear above a gradient of +30% and below a gradient of -30%, respectively. Wint was constant within each speed from a gradient of -15% to level running. This was the result of a nearly constant stride frequency at all negative gradients. The constancy of Wint within this gradient range implies that Wint has no role in determining the optimum gradient. The metabolic cost C was predicted from the mechanical experimental data according to the following equation: [formula: see text] where eff- (0.80), eff+ (0.18) and effi (0.30) are the efficiencies of W-ext, W+ext and Wint, respectively, and el- and el+ represent the amounts of stored and released elastic energy, which are assumed to be 55J step-1. The predicted C versus gradient curve coincides with the curve obtained from metabolic measurements. We conclude that W+ext/W-ext partitioning and the eff+/eff- ratio, i.e. the different efficiency of the muscles during acceleration and braking, explain the metabolic optimum gradient for running of about -10%.

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Year:  1994        PMID: 7964412     DOI: 10.1242/jeb.195.1.211

Source DB:  PubMed          Journal:  J Exp Biol        ISSN: 0022-0949            Impact factor:   3.312


  44 in total

1.  The optimal locomotion on gradients: walking, running or cycling?

Authors:  L P Ardigò; F Saibene; A E Minetti
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2.  Influence of mechanical and metabolic strain on the oxygen consumption slow component during forward pulled running.

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3.  Biomechanical analysis of running in weightlessness on a treadmill equipped with a subject loading system.

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4.  Optical modulation of locomotion and energy expenditure at preferred transition speed.

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Journal:  Exp Brain Res       Date:  2008-06-06       Impact factor: 1.972

5.  The biomechanics of skipping gaits: a third locomotion paradigm?

Authors:  A E Minetti
Journal:  Proc Biol Sci       Date:  1998-07-07       Impact factor: 5.349

Review 6.  The energy cost of sprint running and the role of metabolic power in setting top performances.

Authors:  Pietro E di Prampero; Alberto Botter; Cristian Osgnach
Journal:  Eur J Appl Physiol       Date:  2014-12-31       Impact factor: 3.078

Review 7.  How Biomechanical Improvements in Running Economy Could Break the 2-hour Marathon Barrier.

Authors:  Wouter Hoogkamer; Rodger Kram; Christopher J Arellano
Journal:  Sports Med       Date:  2017-09       Impact factor: 11.136

8.  The energy cost of shuttle running.

Authors:  Antonio Buglione; Pietro Enrico di Prampero
Journal:  Eur J Appl Physiol       Date:  2013-01-09       Impact factor: 3.078

9.  A stability-based mechanism for hysteresis in the walk-trot transition in quadruped locomotion.

Authors:  Shinya Aoi; Daiki Katayama; Soichiro Fujiki; Nozomi Tomita; Tetsuro Funato; Tsuyoshi Yamashita; Kei Senda; Kazuo Tsuchiya
Journal:  J R Soc Interface       Date:  2013-02-06       Impact factor: 4.118

10.  Influence of the world's most challenging mountain ultra-marathon on energy cost and running mechanics.

Authors:  Gianluca Vernillo; Aldo Savoldelli; Andrea Zignoli; Pietro Trabucchi; Barbara Pellegrini; Grégoire P Millet; Federico Schena
Journal:  Eur J Appl Physiol       Date:  2014-01-30       Impact factor: 3.078

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