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Fast and slow processes underlie the selection of both step frequency and walking speed
Author(s) -
Renato Pagliara,
Mark Snaterse,
J. Maxwell Donelan
Publication year - 2014
Publication title -
journal of experimental biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.367
H-Index - 185
eISSN - 1477-9145
pISSN - 0022-0949
DOI - 10.1242/jeb.105270
Subject(s) - selection (genetic algorithm) , preferred walking speed , computer science , neuroscience , biology , artificial intelligence , physiology
People prefer gaits that minimize their energetic cost. Research focused on step frequency selection suggests that a fast predictive process and a slower optimization process underlie this energy optimization. Our purpose in this study was to test whether the mechanisms controlling step frequency selection are used more generally to select one of the most relevant characteristics of walking - preferred speed. To accomplish this, we contrasted the dynamic adjustments in speed following perturbations to step frequency against the dynamic adjustments in step frequency following perturbations to speed. Despite the use of different perturbations and contexts, we found that the responses were very similar. In both experiments, subjects responded to perturbations by first rapidly changing their speed or step frequency towards their preferred pattern, and then slowly adjusting their gait to converge onto their preferred pattern. We measured similar response times for both the fast processes (1.4±0.3 versus 2.7±0.6 s) and the slow processes (74.2±25.4 versus 79.7±20.2 s). We also found that the fast process, although quite variable in amplitude, dominated the adjustments in both speed and step frequency. These distinct but complementary experiments demonstrate that people appear to rely heavily on prediction to rapidly select the most relevant aspects of their preferred gait and then gradually fine-tune that selection, perhaps using direct optimization of energetic cost.

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