Literature DB >> 22298829

Fast visual prediction and slow optimization of preferred walking speed.

Shawn M O'Connor1, J Maxwell Donelan.   

Abstract

People prefer walking speeds that minimize energetic cost. This may be accomplished by directly sensing metabolic rate and adapting gait to minimize it, but only slowly due to the compounded effects of sensing delays and iterative convergence. Visual and other sensory information is available more rapidly and could help predict which gait changes reduce energetic cost, but only approximately because it relies on prior experience and an indirect means to achieve economy. We used virtual reality to manipulate visually presented speed while 10 healthy subjects freely walked on a self-paced treadmill to test whether the nervous system beneficially combines these two mechanisms. Rather than manipulating the speed of visual flow directly, we coupled it to the walking speed selected by the subject and then manipulated the ratio between these two speeds. We then quantified the dynamics of walking speed adjustments in response to perturbations of the visual speed. For step changes in visual speed, subjects responded with rapid speed adjustments (lasting <2 s) and in a direction opposite to the perturbation and consistent with returning the visually presented speed toward their preferred walking speed, when visual speed was suddenly twice (one-half) the walking speed, subjects decreased (increased) their speed. Subjects did not maintain the new speed but instead gradually returned toward the speed preferred before the perturbation (lasting >300 s). The timing and direction of these responses strongly indicate that a rapid predictive process informed by visual feedback helps select preferred speed, perhaps to complement a slower optimization process that seeks to minimize energetic cost.

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Year:  2012        PMID: 22298829     DOI: 10.1152/jn.00866.2011

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  21 in total

1.  Walking on a moving surface: energy-optimal walking motions on a shaky bridge and a shaking treadmill can reduce energy costs below normal.

Authors:  Varun Joshi; Manoj Srinivasan
Journal:  Proc Math Phys Eng Sci       Date:  2015-02-08       Impact factor: 2.704

2.  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

3.  Trading Symmetry for Energy Cost During Walking in Healthy Adults and Persons Poststroke.

Authors:  Ryan T Roemmich; Kristan A Leech; Anthony J Gonzalez; Amy J Bastian
Journal:  Neurorehabil Neural Repair       Date:  2019-06-18       Impact factor: 3.919

4.  Split-arm swinging: the effect of arm swinging manipulation on interlimb coordination during walking.

Authors:  Moshe Bondi; Gabi Zeilig; Ayala Bloch; Alfonso Fasano; Meir Plotnik
Journal:  J Neurophysiol       Date:  2017-05-10       Impact factor: 2.714

5.  Dynamic modulation of visual and electrosensory gains for locomotor control.

Authors:  Erin E Sutton; Alican Demir; Sarah A Stamper; Eric S Fortune; Noah J Cowan
Journal:  J R Soc Interface       Date:  2016-05       Impact factor: 4.118

6.  Retinal optic flow during natural locomotion.

Authors:  Jonathan Samir Matthis; Karl S Muller; Kathryn L Bonnen; Mary M Hayhoe
Journal:  PLoS Comput Biol       Date:  2022-02-22       Impact factor: 4.475

Review 7.  Proprioceptive feedback and preferred patterns of human movement.

Authors:  Jesse C Dean
Journal:  Exerc Sport Sci Rev       Date:  2013-01       Impact factor: 6.230

8.  Reproductive costs for everyone: how female loads impact human mobility strategies.

Authors:  Cara M Wall-Scheffler; Marcella J Myers
Journal:  J Hum Evol       Date:  2013-03-05       Impact factor: 3.895

9.  The Determinants of the Preferred Walking Speed in Individuals with Obesity.

Authors:  Aitor Fernández Menéndez; Mathieu Saubade; Didier Hans; Grégoire P Millet; Davide Malatesta
Journal:  Obes Facts       Date:  2019-09-10       Impact factor: 3.942

10.  Speed-related but not detrended gait variability increases with more sensitive self-paced treadmill controllers at multiple slopes.

Authors:  Cesar R Castano; Helen J Huang
Journal:  PLoS One       Date:  2021-05-07       Impact factor: 3.240

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