Evidence map›Paper›PMID 37274172›Full record

ArticleFrontiers in bioengineering and biotechnology2023

Modeling of active skeletal muscles: a 3D continuum approach incorporating multiple muscle interactions.

Wei Zeng, Donald R Hume, Yongtao Lu, Clare K Fitzpatrick, Colton Babcock, Casey A Myers, Paul J Rullkoetter, Kevin B Shelburne

Open access · goldAbstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.9field-weighted citation impact, top 16% 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

8 citing papers in PubMed, 17 citations in OpenAlex.

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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

8 authors at 4 institutions in 2 countries.

Wei ZengCenter for Orthopaedic Biomechanics, University of Denver, Denver, CO, United States.
Donald R HumeCenter for Orthopaedic Biomechanics, University of Denver, Denver, CO, United States.
Yongtao LuDepartment of Engineering Mechanics, Dalian University of Technology, Dalian, China.
Clare K FitzpatrickMechanical and Biomedical Engineering, Boise State University, Boise, ID, United States.
Colton BabcockMechanical and Biomedical Engineering, Boise State University, Boise, ID, United States.
Casey A MyersCenter for Orthopaedic Biomechanics, University of Denver, Denver, CO, United States.
Paul J RullkoetterCenter for Orthopaedic Biomechanics, University of Denver, Denver, CO, United States.
Kevin B ShelburneCenter for Orthopaedic Biomechanics, University of Denver, Denver, CO, United States.
University of Denver · USBoise State University · USDalian University of Technology · CNNew York Institute of Technology · 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
NIAMS NIH HHS U01 AR072989
6 · The paper itself

Abstract

Skeletal muscles have a highly organized hierarchical structure, whose main function is to generate forces for movement and stability. To understand the complex heterogeneous behaviors of muscles, computational modeling has advanced as a non-invasive approach to evaluate relevant mechanical quantities. Aiming to improve musculoskeletal predictions, this paper presents a framework for modeling 3D deformable muscles that includes continuum constitutive representation, parametric determination, model validation, fiber distribution estimation, and integration of multiple muscles into a system level for joint motion simulation. The passive and active muscle properties were modeled based on the strain energy approach with Hill-type hyperelastic constitutive laws. A parametric study was conducted to validate the model using experimental datasets of passive and active rabbit leg muscles. The active muscle model with calibrated material parameters was then implemented to simulate knee bending during a squat with multiple quadriceps muscles. A computational fluid dynamics (CFD) fiber simulation approach was utilized to estimate the fiber arrangements for each muscle, and a cohesive contact approach was applied to simulate the interactions among muscles. The single muscle simulation results showed that both passive and active muscle elongation responses matched the range of the testing data. The dynamic simulation of knee flexion and extension showed the predictive capability of the model for estimating the active quadriceps responses, which indicates that the presented modeling pipeline is effective and stable for simulating multiple muscle configurations. This work provided an effective framework of a 3D continuum muscle model for complex muscle behavior simulation, which will facilitate additional computational and experimental studies of skeletal muscle mechanics. This study will offer valuable insight into the future development of multiscale neuromuscular models and applications of these models to a wide variety of relevant areas such as biomechanics and clinical research.

Indexed as

active skeletal musclefinite element analysisHill-type muscle modelmuscle interactionsparametric studyquadriceps

Identifiers

PMID37274172
PMCPMC10234509
OpenAlexW4377023170

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.