Literature DB >> 17766303

Mechanical power and efficiency of level walking with different stride rates.

Brian R Umberger1, Philip E Martin.   

Abstract

Walking humans prefer to use the stride rate that results in the lowest rate of metabolic energy expenditure. Mechanical power requirements have been suggested to underlie the metabolic response, but mechanical power is consistently reported to be minimal at stride rates 20-30% lower than preferred. This may be due to limitations in how total mechanical power has been computed, as well as a failure to account for the efficiency with which muscular work is done. We investigated how mechanical power and efficiency depend on stride rate in walking, with both quantities computed from the work done by the hip, knee and ankle joint moments. Our hypotheses were that mechanical power and efficiency are both optimized at the preferred stride rate, which would explain why metabolic energy expenditure is minimized at this rate. Contrary to our hypotheses, mechanical power curves exhibited plateaus that spanned stride rates lower than preferred (predicted optima: 11-12% below preferred), while net mechanical efficiency exhibited a plateau that spanned stride rates higher than preferred (predicted optimum: 8% above preferred). As expected, preferred stride rate (54.3 strides min(-1)) was not different from the stride rate that minimized net metabolic energy expenditure (predicted optimum: 0.2% above preferred). Given that mechanical power and mechanical efficiency exhibited plateaus on opposite sides of the preferred stride rate, the preferred rate in walking likely represents a compromise between these two factors. This may also explain the relative flatness of the curve for metabolic rate in the vicinity of the preferred stride rate.

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Year:  2007        PMID: 17766303     DOI: 10.1242/jeb.000950

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


  54 in total

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2.  Similar muscles contribute to horizontal and vertical acceleration of center of mass in forward and backward walking: implications for neural control.

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3.  Stance and swing phase costs in human walking.

Authors:  Brian R Umberger
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4.  Age and muscle strength mediate the age-related biomechanical plasticity of gait.

Authors:  Tibor Hortobágyi; Patrick Rider; Allison H Gruber; Paul DeVita
Journal:  Eur J Appl Physiol       Date:  2016-02-11       Impact factor: 3.078

5.  Contribution of blood oxygen and carbon dioxide sensing to the energetic optimization of human walking.

Authors:  Jeremy D Wong; Shawn M O'Connor; Jessica C Selinger; J Maxwell Donelan
Journal:  J Neurophysiol       Date:  2017-06-21       Impact factor: 2.714

6.  The relationships between muscle, external, internal and joint mechanical work during normal walking.

Authors:  Kotaro Sasaki; Richard R Neptune; Steven A Kautz
Journal:  J Exp Biol       Date:  2009-03       Impact factor: 3.312

7.  Proprioceptive feedback contributes to the adaptation toward an economical gait pattern.

Authors:  Jill E Hubbuch; Blake W Bennett; Jesse C Dean
Journal:  J Biomech       Date:  2015-04-23       Impact factor: 2.712

8.  Walk-run transition in young and older adults: with special reference to the cardio-respiratory responses.

Authors:  P T V Farinatti; W D Monteiro
Journal:  Eur J Appl Physiol       Date:  2010-02-03       Impact factor: 3.078

9.  Forward dynamics simulations provide insight into muscle mechanical work during human locomotion.

Authors:  Richard R Neptune; Craig P McGowan; Steven A Kautz
Journal:  Exerc Sport Sci Rev       Date:  2009-10       Impact factor: 6.230

10.  Mechanotransduction in primary human osteoarthritic chondrocytes is mediated by metabolism of energy, lipids, and amino acids.

Authors:  Donald L Zignego; Jonathan K Hilmer; Ronald K June
Journal:  J Biomech       Date:  2015-10-31       Impact factor: 2.712

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