Evidence map›Paper›PMID 32812382›Full record

ArticleInternational journal for numerical methods in biomedical engineering2020

ReadySim: A computational framework for building explicit finite element musculoskeletal simulations directly from motion laboratory data.

Donald R Hume, Paul J Rullkoetter, Kevin B Shelburne

Open access · greenAbstract read
In one paragraph

Article in International journal for numerical methods in biomedical engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.4field-weighted citation impact, top 41% 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

7 citing papers in PubMed, 7 citations in OpenAlex.

  1. Rapid personalized computational modeling of the wrist.Medical engineering & physics · 2026
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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

3 authors at 1 institution in 1 country.

Donald R HumeCenter for Orthopaedic Biomechanics, University of Denver, Denver, Colorado, USA.ORCID 0000-0001-9081-358X
Paul J RullkoetterCenter for Orthopaedic Biomechanics, University of Denver, Denver, Colorado, USA.
Kevin B ShelburneCenter for Orthopaedic Biomechanics, University of Denver, Denver, Colorado, USA.
University of Denver · US

Funding

A Lower Extremity Neuromusculoskeletal Human Simulator: Addressing Multiscale ChallengesU01AR072989 · NIAMS · UNIVERSITY OF DENVER (COLORADO SEMINARY) · PI SHELBURNE, KEVIN B · 2018 to 2021
$1.9M
A Multi-Scale Finite Element Musculoskeletal Modeling Framework Applied to CurrenR01EB015497 · NIBIB · UNIVERSITY OF DENVER (COLORADO SEMINARY) · PI SHELBURNE, KEVIN B · 2012 to 2015
$1.1M
NIAMS NIH HHS U01 AR072989NIBIB NIH HHS R01 EB015497
6 · The paper itself

Abstract

Musculoskeletal modeling allows researchers insight into joint mechanics which might not otherwise be obtainable through in vivo or in vitro studies. Common musculoskeletal modeling techniques involve rigid body dynamics software which often employ simplified joint representations. These representations have proven useful but are limited in performing single-framework deformable analyzes in structures of interest. Musculoskeletal finite element (MSFE) analysis allows for representation of structures in sufficient detail to obtain accurate solutions of the internal stresses and strains including complex contact conditions and material representations. Studies which performed muscle force optimization directly in a finite element framework were often limited in complexity to minimize computational time. Recent advances in computational efficiency and control schemes for muscle force prediction have made these solutions more practical. Yet, the formulation of subject-specific simulations remains a challenging problem. The objectives of this work were to develop an open-source computational framework to build and run simulations which (a) scale the size of MSFE models and efficiently estimate (b) joint kinematics and (c) muscle forces from human motion data collected in a typical gait laboratory. A computational framework was built using MATLAB and Python to interface with model input and output files. The software uses laboratory marker data to scale model segment lengths and estimate joint kinematics. Concurrent muscle force and tissue strain estimations are performed based on the estimated kinematics and ground reaction forces. This software will improve the usability and consistency of single-framework MSFE simulations. Both software and template model are made freely available on SimTK.Novelty Statement Single framework musculoskeletal modeling directly in a finite element environment for muscle force estimation and tissue strain analysis. Open dissemination of unilateral musculoskeletal finite element model and software used in manuscript.

Indexed as

LaboratoriesModels, BiologicalBiomechanical PhenomenaFinite Element AnalysisGaitHumansKnee Jointkinematicsknee mechanicsligamentmultiscale modeling

Identifiers

PMID32812382
PMCPMC8265519
OpenAlexW3073794180

What OpenQuestion holds

Textmetadata
LicenceTDM
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.