Evidence map›Paper›PMID 31431186›Full record

ArticleJournal of the Royal Society, Interface2019

Rapid predictive simulations with complex musculoskeletal models suggest that diverse healthy and pathological human gaits can emerge from similar control strategies.

Antoine Falisse, Gil Serrancolí, Christopher L Dembia, Joris Gillis, Ilse Jonkers, Friedl De Groote

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 104 papers.

0numbers the graph read from it
0cells of the map it votes in
104citing papers in PubMed
–field-weighted citation impact
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

104 citing papers in PubMed.

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44 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

6 authors.

Antoine FalisseDepartment of Movement Sciences, KU Leuven, Leuven, Belgium.
Gil SerrancolíDepartment of Mechanical Engineering, Universitat Politècnica de Catalunya, Barcelona, Catalunya, Spain.
Christopher L DembiaDepartment of Mechanical Engineering, Stanford University, Stanford, CA, USA.
Joris GillisDepartment of Mechanical Engineering, KU Leuven, Leuven, Belgium.
Ilse JonkersDepartment of Movement Sciences, KU Leuven, Leuven, Belgium.
Friedl De GrooteDepartment of Movement Sciences, KU Leuven, Leuven, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Physics-based predictive simulations of human movement have the potential to support personalized medicine, but large computational costs and difficulties to model control strategies have limited their use. We have developed a computationally efficient optimal control framework to predict human gaits based on optimization of a performance criterion without relying on experimental data. The framework generates three-dimensional muscle-driven simulations in 36 min on average-more than 20 times faster than existing simulations-by using direct collocation, implicit differential equations and algorithmic differentiation. Using this framework, we identified a multi-objective performance criterion combining energy and effort considerations that produces physiologically realistic walking gaits. The same criterion also predicted the walk-to-run transition and clinical gait deficiencies caused by muscle weakness and prosthesis use, suggesting that diverse healthy and pathological gaits can emerge from the same control strategy. The ability to predict the mechanics and energetics of a broad range of gaits with complex three-dimensional musculoskeletal models will allow testing novel hypotheses about gait control and hasten the development of optimal treatments for neuro-musculoskeletal disorders.

Indexed as

Computer SimulationModels, BiologicalBiomechanical PhenomenaGaitHumansNeuromuscular Diseasesbiomechanicslocomotionoptimal controlthree-dimensional

Identifiers

PMID31431186
PMCPMC6731507

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Registered trials

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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.