Literature DB >> 30630624

A lower extremity model for muscle-driven simulation of activity using explicit finite element modeling.

Donald R Hume1, Alessandro Navacchia2, Paul J Rullkoetter2, Kevin B Shelburne2.   

Abstract

A key strength of computational modeling is that it can provide estimates of muscle, ligament, and joint loads, stresses, and strains through non-invasive means. However, simulations that can predict the forces in the muscles during activity while maintaining sufficient complexity to realistically represent the muscles and joint structures can be computationally challenging. For this reason, the current state of the art is to apply separate rigid-body dynamic and finite-element (FE) analyses in series. However, the use of two or more disconnected models often fails to capture key interactions between the joint-level and whole-body scales. Single framework MSFE models have the potential to overcome the limitations associated with disconnected models in series. The objectives of the current study were to create a multi-scale FE model of the human lower extremity that combines optimization, dynamic muscle modeling, and structural FE analysis in a single framework and to apply this framework to evaluate the mechanics of healthy knee specimens during two activities. Two subject-specific FE models (Model 1, Model 2) of the lower extremity were developed in ABAQUS/Explicit including detailed representations of the muscles. Muscle forces, knee joint loading, and articular contact were calculated for two activities using an inverse dynamics approach and static optimization. Quadriceps muscle forces peaked at the onset of chair rise (2174 N, 1962 N) and in early stance phase (510 N, 525 N), while gait saw peak forces in the hamstrings (851 N, 868 N) in midstance. Joint forces were similar in magnitude to available telemetric patient data. This study demonstrates the feasibility of detailed quasi-static, muscle-driven simulations in an FE framework.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Finite element; Gait; Knee; Muscle; Musculoskeletal modeling; Squatting

Mesh:

Year:  2019        PMID: 30630624      PMCID: PMC6361714          DOI: 10.1016/j.jbiomech.2018.12.040

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  4 in total

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

Authors:  Donald R Hume; Paul J Rullkoetter; Kevin B Shelburne
Journal:  Int J Numer Method Biomed Eng       Date:  2020-09-01       Impact factor: 2.747

2.  Integration of neural architecture within a finite element framework for improved neuromusculoskeletal modeling.

Authors:  Victoria L Volk; Landon D Hamilton; Donald R Hume; Kevin B Shelburne; Clare K Fitzpatrick
Journal:  Sci Rep       Date:  2021-11-26       Impact factor: 4.379

3.  Hamstrings Contraction Regulates the Magnitude and Timing of the Peak ACL Loading During the Drop Vertical Jump in Female Athletes.

Authors:  Ryo Ueno; Alessandro Navacchia; Nathan D Schilaty; Gregory D Myer; Timothy E Hewett; Nathaniel A Bates
Journal:  Orthop J Sports Med       Date:  2021-09-29

4.  Anterior Cruciate Ligament Loading Increases With Pivot-Shift Mechanism During Asymmetrical Drop Vertical Jump in Female Athletes.

Authors:  Ryo Ueno; Alessandro Navacchia; Nathan D Schilaty; Gregory D Myer; Timothy E Hewett; Nathaniel A Bates
Journal:  Orthop J Sports Med       Date:  2021-03-09
  4 in total

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