ArticlePLoS computational biology2022
Adaptive multi-objective control explains how humans make lateral maneuvers while walking.
Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- How visual context influences lateral stepping regulation while walking on winding paths.Journal of neurophysiology · 2026Article
- Visual Context Influences Lateral Balance While Walking on Winding Paths.bioRxiv : the preprint server for biology · 2026Article
- Adapting lateral stepping control to walk on winding paths.Journal of biomechanics · 2025Article
- Probability of lateral instability while walking on winding paths.Journal of biomechanics · 2024Article
- A model of task-level human stepping regulation yields semistable walking.Journal of the Royal Society, Interface · 2024Article
- A model of task-level human stepping regulation yields semistable walking.bioRxiv : the preprint server for biology · 2024Article
- How Healthy Older Adults Enact Lateral Maneuvers While Walking.Gait & posture · 2024Article
- Generalizing stepping concepts to non-straight walking.Journal of biomechanics · 2023Article
- How older adults regulate lateral stepping on narrowing walking paths.Journal of biomechanics · 2023Article
- Gait-phase specific transverse-plane momenta generation during pre-planned and late-cued 90 degree turns while walking.Scientific reports · 2023Article
- Adaptive multi-objective control explains how humans make lateral maneuvers while walking.PLoS computational biology · 2022Article
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Authors and funding
3 authors.
Funding
Abstract
To successfully traverse their environment, humans often perform maneuvers to achieve desired task goals while simultaneously maintaining balance. Humans accomplish these tasks primarily by modulating their foot placements. As humans are more unstable laterally, we must better understand how humans modulate lateral foot placement. We previously developed a theoretical framework and corresponding computational models to describe how humans regulate lateral stepping during straight-ahead continuous walking. We identified goal functions for step width and lateral body position that define the walking task and determine the set of all possible task solutions as Goal Equivalent Manifolds (GEMs). Here, we used this framework to determine if humans can regulate lateral stepping during non-steady-state lateral maneuvers by minimizing errors consistent with these goal functions. Twenty young healthy adults each performed four lateral lane-change maneuvers in a virtual reality environment. Extending our general lateral stepping regulation framework, we first re-examined the requirements of such transient walking tasks. Doing so yielded new theoretical predictions regarding how steps during any such maneuver should be regulated to minimize error costs, consistent with the goals required at each step and with how these costs are adapted at each step during the maneuver. Humans performed the experimental lateral maneuvers in a manner consistent with our theoretical predictions. Furthermore, their stepping behavior was well modeled by allowing the parameters of our previous lateral stepping models to adapt from step to step. To our knowledge, our results are the first to demonstrate humans might use evolving cost landscapes in real time to perform such an adaptive motor task and, furthermore, that such adaptation can occur quickly-over only one step. Thus, the predictive capabilities of our general stepping regulation framework extend to a much greater range of walking tasks beyond just normal, straight-ahead walking.
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