ArticleFrontiers in bioengineering and biotechnology2022
High-level motor planning allows flexible walking at different gait patterns in a neuromechanical model.
Article in Frontiers in bioengineering and biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Methods for integrating postural control into biomechanical human simulations: a systematic review.Journal of neuroengineering and rehabilitation · 2023Pooled it
- A model of the cerebellum generates gait adaptations in a reflex-based neuromusculoskeletal model during split-belt walking.Journal of neuroengineering and rehabilitation · 2025Article
- A model of the cerebellum generates gait adaptations in a reflex-based neuromusculoskeletal model during split-belt walking.bioRxiv : the preprint server for biology · 2025Article
- Controlling a simple model of bipedal walking to adapt to a wide range of target step lengths and step frequencies.PloS one · 2025Article
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Authors and funding
3 authors.
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Abstract
Humans can freely adopt gait parameters like walking speed, step length, or cadence on the fly when walking. Planned movement that can be updated online to account for changes in the environment rather than having to rely on habitual, reflexive control that is adapted over long timescales. Here we present a neuromechanical model that accounts for this flexibility by combining movement goals and motor plans on a kinematic task level with low-level spinal feedback loops. We show that the model can walk at a wide range of different gait patterns by choosing a small number of high-level control parameters representing a movement goal. A larger number of parameters governing the low-level reflex loops in the spinal cord, on the other hand, remain fixed. We also show that the model can generalize the learned behavior by recombining the high-level control parameters and walk with gait patterns that it had not encountered before. Furthermore, the model can transition between different gaits without the loss of balance by switching to a new set of control parameters in real time.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.