Evidence map›Paper›PMID 31589597›Full record

ArticlePLoS computational biology2019

Predicting gait adaptations due to ankle plantarflexor muscle weakness and contracture using physics-based musculoskeletal simulations.

Carmichael F Ong, Thomas Geijtenbeek, Jennifer L Hicks, Scott L Delp

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed, 1 pooled it
8.8field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

70 citing papers in PubMed, 1 synthesis or guideline pooled it, 184 citations in OpenAlex.

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  20. Perturbation-based estimation of within-stride cycle metabolic cost.Journal of neuroengineering and rehabilitation · 2024
    Article

10 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

Carmichael F OngDepartment of Bioengineering, Stanford University, Stanford, California, United States of America.ORCID 0000-0002-0589-5347
Thomas GeijtenbeekDepartment of Biomechatronics & Human-Machine Control, Delft University of Technology, Delft, The Netherlands.
Jennifer L HicksDepartment of Bioengineering, Stanford University, Stanford, California, United States of America.ORCID 0000-0002-2516-9334
Scott L DelpDepartment of Bioengineering, Stanford University, Stanford, California, United States of America.ORCID 0000-0002-9643-7551
Stanford University · USDelft University of Technology · NL

Funding

Training CoreU54EB020405 · NIBIB · STANFORD UNIVERSITY · PI DELP, SCOTT L · 2014 to 2018
$11.6M
Tech-DevelopmentP2CHD065690 · NICHD · STANFORD UNIVERSITY · PI DELP, SCOTT L · 2015 to 2019
$5.4M
NIBIB NIH HHS U54 EB020405NICHD NIH HHS P2C HD065690
6 · The paper itself

Abstract

Deficits in the ankle plantarflexor muscles, such as weakness and contracture, occur commonly in conditions such as cerebral palsy, stroke, muscular dystrophy, Charcot-Marie-Tooth disease, and sarcopenia. While these deficits likely contribute to observed gait pathologies, determining cause-effect relationships is difficult due to the often co-occurring biomechanical and neural deficits. To elucidate the effects of weakness and contracture, we systematically introduced isolated deficits into a musculoskeletal model and generated simulations of walking to predict gait adaptations due to these deficits. We trained a planar model containing 9 degrees of freedom and 18 musculotendon actuators to walk using a custom optimization framework through which we imposed simple objectives, such as minimizing cost of transport while avoiding falling and injury, and maintaining head stability. We first generated gaits at prescribed speeds between 0.50 m/s and 2.00 m/s that reproduced experimentally observed kinematic, kinetic, and metabolic trends for walking. We then generated a gait at self-selected walking speed; quantitative comparisons between our simulation and experimental data for joint angles, joint moments, and ground reaction forces showed root-mean-squared errors of less than 1.6 standard deviations and normalized cross-correlations above 0.8 except for knee joint moment trajectories. Finally, we applied mild, moderate, and severe levels of muscle weakness or contracture to either the soleus (SOL) or gastrocnemius (GAS) or both of these major plantarflexors (PF) and retrained the model to walk at a self-selected speed. The model was robust to all deficits, finding a stable gait in all cases. Severe PF weakness caused the model to adopt a slower, "heel-walking" gait. Severe contracture of only SOL or both PF yielded similar results: the model adopted a "toe-walking" gait with excessive hip and knee flexion during stance. These results highlight how plantarflexor weakness and contracture may contribute to observed gait patterns.

Indexed as

Adaptation, PhysiologicalAnkleBiomechanical PhenomenaComputer SimulationForecastingGaitGait AnalysisHumansModels, BiologicalMuscle, SkeletalMuscle WeaknessWalking

Identifiers

PMID31589597
PMCPMC6797212
OpenAlexW2979118233

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.