Evidence map›Paper›PMID 26245321›Full record

ArticleJournal of neurophysiology2015

Modeling and simulating the neuromuscular mechanisms regulating ankle and knee joint stiffness during human locomotion.

Massimo Sartori, Marco Maculan, Claudio Pizzolato, Monica Reggiani, Dario Farina

Registry-linked trialAbstract read
In one paragraph

Article in Journal of neurophysiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04778852 (Quantitative Assessment of Training Effects Using a Wearable Exoskeleton in Parkinson Disease Patients), which is not on this map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing 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.

NCT04778852 naunknown statusnot on this mapstarted 2020, after this paper: background citation

Quantitative Assessment of Training Effects Using a Wearable Exoskeleton in Parkinson Disease Patients

TypeinterventionalSponsorUniversity of PadovaRan2020 to 2023Enrolled50ConditionsParkinson DiseaseArmsExperimental: EksoGT, Functional kinematic training
3 · Its place in the literature

Who cites it

37 citing papers in PubMed.

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  15. Assisting walking balance using a bio-inspired exoskeleton controller.Journal of neuroengineering and rehabilitation · 2023
    Article
  16. Article
  17. Article
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  20. Review
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

5 authors.

Massimo SartoriUniversity Medical Center Goettingen, Georg-August University, Goettingen, Germany; massimo.srt@gmail.com.
Marco MaculanDepartment of Management and Engineering, University of Padova, Padova, Italy; and.
Claudio PizzolatoCentre for Musculoskeletal Research, Griffith University, Queensland, Australia.
Monica ReggianiDepartment of Management and Engineering, University of Padova, Padova, Italy; and.
Dario FarinaUniversity Medical Center Goettingen, Georg-August University, Goettingen, Germany;

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This work presents an electrophysiologically and dynamically consistent musculoskeletal model to predict stiffness in the human ankle and knee joints as derived from the joints constituent biological tissues (i.e., the spanning musculotendon units). The modeling method we propose uses electromyography (EMG) recordings from 13 muscle groups to drive forward dynamic simulations of the human leg in five healthy subjects during overground walking and running. The EMG-driven musculoskeletal model estimates musculotendon and resulting joint stiffness that is consistent with experimental EMG data as well as with the experimental joint moments. This provides a framework that allows for the first time observing 1) the elastic interplay between the knee and ankle joints, 2) the individual muscle contribution to joint stiffness, and 3) the underlying co-contraction strategies. It provides a theoretical description of how stiffness modulates as a function of muscle activation, fiber contraction, and interacting tendon dynamics. Furthermore, it describes how this differs from currently available stiffness definitions, including quasi-stiffness and short-range stiffness. This work offers a theoretical and computational basis for describing and investigating the neuromuscular mechanisms underlying human locomotion.

Indexed as

Models, BiologicalAccelerometryAdultAnkle JointBiomechanical PhenomenaElasticityElectromyographyHumansKnee JointLegMaleMuscle ContractionMuscle Fibers, SkeletalMuscle, SkeletalRunningSignal Processing, Computer-Assistedcomplianceelectromyographyhuman legneuromusculoskeletal modelingstiffness

Identifiers

PMID26245321
PMCPMC4620138

What OpenQuestion holds

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Registered trials

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.