Dataset Information

Correlations of pelvis state to foot placement do not imply within-step active control.

ABSTRACT: Experimental studies of human walking have shown that within an individual step, variations in the center of mass (CoM) state can predict corresponding variations in the next foot placement. This has been interpreted by some to indicate the existence of active control in which the nervous system uses the CoM state at or near mid-stance to regulate subsequent foot placement. However, the passive dynamics of the moving body and/or moving limbs also contribute (perhaps strongly) to foot placement, and thus to its variation. The extent to which correlations of CoM state to foot placement reflect the effects of within-step active control, those of passive dynamics, or some combination of both, remains an important and still open question. Here, we used an open-loop-stable 2D walking model to show that this predictive ability cannot by itself be taken as evidence of within-step active control. In our simulations, we too find high correlations between the CoM state and subsequent foot placement, but these correlations are entirely due to passive dynamics as our system has no active control, either within a step or between steps. This demonstrates that any inferences made from such correlations about within-step active control require additional supporting evidence beyond the correlations themselves. Thus, these within-step predictive correlations leave unresolved the relative importance of within-step active control as compared to passive dynamics, meaning that such methods should be used to characterize control in human walking only with caution.

SUBMITTER: Patil NS

PROVIDER: S-EPMC7171510 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Correlations of pelvis state to foot placement do not imply within-step active control.

Patil Navendu S NS Dingwell Jonathan B JB Cusumano Joseph P JP

Journal of biomechanics 20191008

Experimental studies of human walking have shown that within an individual step, variations in the center of mass (CoM) state can predict corresponding variations in the next foot placement. This has been interpreted by some to indicate the existence of active control in which the nervous system uses the CoM state at or near mid-stance to regulate subsequent foot placement. However, the passive dynamics of the moving body and/or moving limbs also contribute (perhaps strongly) to foot placement, ...[more]

PMID: 31668906

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Project description:A fundamental question in human motor neuroscience is to determine how the nervous system generates goal-directed movements despite inherent physiological noise and redundancy. Walking exhibits considerable variability and equifinality of task solutions. Existing models of bipedal walking do not yet achieve both continuous dynamic balance control and the equifinality of foot placement humans exhibit. Appropriate computational models are critical to disambiguate the numerous possibilities of how to regulate stepping movements to achieve different walking goals. Here, we extend a theoretical and computational Goal Equivalent Manifold (GEM) framework to generate predictive models, each posing a different experimentally testable hypothesis. These models regulate stepping movements to achieve any of three hypothesized goals, either alone or in combination: maintain lateral position, maintain lateral speed or "heading", and/or maintain step width. We compared model predictions against human experimental data. Uni-objective control models demonstrated clear redundancy between stepping variables, but could not replicate human stepping dynamics. Most multi-objective control models that balanced maintaining two of the three hypothesized goals also failed to replicate human stepping dynamics. However, multi-objective models that strongly prioritized regulating step width over lateral position did successfully replicate all of the relevant step-to-step dynamics observed in humans. Independent analyses confirmed this control was consistent with linear error correction and replicated step-to-step dynamics of individual foot placements. Thus, the regulation of lateral stepping movements is inherently multi-objective and balances task-specific trade-offs between competing task goals. To determine how people walk in their environment requires understanding both walking biomechanics and how the nervous system regulates movements from step-to-step. Analogous to mechanical "templates" of locomotor biomechanics, our models serve as "control templates" for how humans regulate stepping movements from each step to the next. These control templates are symbiotic with well-established mechanical templates, providing complimentary insights into walking regulation.

Dataset Information

Correlations of pelvis state to foot placement do not imply within-step active control.

Publications

Correlations of pelvis state to foot placement do not imply within-step active control.

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