Do Humans Optimally Exploit Redundancy to Control Step Variability in Walking?

dc.creatorDingwell, Jonathan B.en
dc.creatorJohn, Jobyen
dc.creatorCusumano, Joseph P.en
dc.date.accessioned2013-06-28T15:53:12Zen
dc.date.available2013-06-28T15:53:12Zen
dc.date.issued2010-07-15en
dc.descriptionJonathan B. Dingwell is with UT Austin, Joby John is with Pennsylvania State University, Joseph P. Cusumano is with Pennsylvania State University.en
dc.description.abstractIt is widely accepted that humans and animals minimize energetic cost while walking. While such principles predict average behavior, they do not explain the variability observed in walking. For robust performance, walking movements must adapt at each step, not just on average. Here, we propose an analytical framework that reconciles issues of optimality, redundancy, and stochasticity. For human treadmill walking, we defined a goal function to formulate a precise mathematical definition of one possible control strategy: maintain constant speed at each stride. We recorded stride times and stride lengths from healthy subjects walking at five speeds. The specified goal function yielded a decomposition of stride-to-stride variations into new gait variables explicitly related to achieving the hypothesized strategy. Subjects exhibited greatly decreased variability for goal-relevant gait fluctuations directly related to achieving this strategy, but far greater variability for goal-irrelevant fluctuations. More importantly, humans immediately corrected goal-relevant deviations at each successive stride, while allowing goal-irrelevant deviations to persist across multiple strides. To demonstrate that this was not the only strategy people could have used to successfully accomplish the task, we created three surrogate data sets. Each tested a specific alternative hypothesis that subjects used a different strategy that made no reference to the hypothesized goal function. Humans did not adopt any of these viable alternative strategies. Finally, we developed a sequence of stochastic control models of stride-to-stride variability for walking, based on the Minimum Intervention Principle. We demonstrate that healthy humans are not precisely “optimal,” but instead consistently slightly over-correct small deviations in walking speed at each stride. Our results reveal a new governing principle for regulating stride-to-stride fluctuations in human walking that acts independently of, but in parallel with, minimizing energetic cost. Thus, humans exploit task redundancies to achieve robust control while minimizing effort and allowing potentially beneficial motor variability.en
dc.description.departmentKinesiology and Health Educationen
dc.description.sponsorshipPartial funding was provided by a Biomedical Engineering Research Grant (grant # RG-02-0354) from the Whitaker Foundation (JBD), by US National Institutes of Health grants 1-R03-HD058942-01 and 1-R21-EB007638-01A1 (JBD), and by National Science Foundation grant 0625764 (JPC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.en
dc.identifier.citationDingwell JB, John J, Cusumano JP (2010) Do Humans Optimally Exploit Redundancy to Control Step Variability in Walking? PLoS Comput Biol 6(7): e1000856. doi:10.1371/journal.pcbi.1000856en
dc.identifier.doi10.1371/journal.pcbi.1000856en
dc.identifier.urihttp://hdl.handle.net/2152/20555en
dc.language.isoengen
dc.publisherPublic Library of Scienceen
dc.rightsAttribution 3.0 United Statesen
dc.rightsCC-BYen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/en
dc.subjectAnalysis of varianceen
dc.subjectAnimal behavioren
dc.subjectBehavioren
dc.subjectHuman movementen
dc.subjectMotor systemen
dc.subjectOptimizationen
dc.subjectSensory physiologyen
dc.subjectWalkingen
dc.titleDo Humans Optimally Exploit Redundancy to Control Step Variability in Walking?en
dc.typeArticleen
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