Evidence map›Paper›PMID 42021378›Full record

ArticleJournal of neuroengineering and rehabilitation2026

Estimating and interpreting how humans prioritize multiple movement goals during walking.

Jordan N Feldman, David Morales Loro, Andrew Chin, Sarah Erickson, Sarah Li, Eliana Bonbrest, Patrick Slade

Abstract read
In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Jordan N FeldmanJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, MA, USA.
David Morales LoroTechnical University of Munich, Munich, Germany.
Andrew ChinJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, MA, USA.
Sarah EricksonJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, MA, USA.
Sarah LiJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, MA, USA.
Eliana BonbrestJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, MA, USA.
Patrick SladeJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, MA, USA. slade@seas.harvard.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWalking requires managing competing movement goals shaped by the demands of everyday activity. Several important goals during overground walking include maintaining a desired walking speed, achieving an intended foot placement, preserving postural and locomotor balance, and reducing energy expenditure. Biomechanical simulation and motor control-based methods use goal-related cost functions or structured models to identify people’s movement priorities but are often restricted to simple movement scenarios and are currently impractical for broad deployment.

methodsHere, we systematically vary four movement goals during an overground walking experiment, characterize the resulting trade-offs in spatiotemporal gait metrics, and show that these trade-offs are sufficient to estimate participants’ perceived ranking of movement goals.

resultsGait metrics across participants became more heterogenous as combinations of movement goal prompts became more complex, suggesting person-specific movement strategies. Participants’ perceived prioritization of movement goals showed systematic associations with corresponding gait metrics, with the strongest relationships observed for visually guided goals such as balance and foot placement. Subject-agnostic regression models estimated the perceived order of importance of movement goals with 21% error, and subject-specific models reduced this error to 11%.

conclusionsThis work establishes an approach for estimation of movement priorities in young, healthy adults using simple gait metrics and provides a framework that could inform future studies beyond the laboratory.

Indexed as

GoalsWalkingAdultBiomechanical PhenomenaFemaleGaitHumansMaleMovementPostural BalanceYoung AdultBiomechanicsDecision makingHuman behavior

Identifiers

PMID42021378
PMCPMC13262477

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.