Literature DB >> 32812382

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

Donald R Hume1, Paul J Rullkoetter1, Kevin B Shelburne1.   

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.
© 2020 John Wiley & Sons Ltd.

Entities:  

Keywords:  kinematics; knee mechanics; ligament; multiscale modeling

Year:  2020        PMID: 32812382      PMCID: PMC8265519          DOI: 10.1002/cnm.3396

Source DB:  PubMed          Journal:  Int J Numer Method Biomed Eng        ISSN: 2040-7939            Impact factor:   2.747


  31 in total

1.  Efficient probabilistic representation of tibiofemoral soft tissue constraint.

Authors:  Mark A Baldwin; Peter J Laz; Joshua Q Stowe; Paul J Rullkoetter
Journal:  Comput Methods Biomech Biomed Engin       Date:  2009-12       Impact factor: 1.763

2.  Concurrent prediction of muscle and tibiofemoral contact forces during treadmill gait.

Authors:  Trent M Guess; Antonis P Stylianou; Mohammad Kia
Journal:  J Biomech Eng       Date:  2014-02       Impact factor: 2.097

3.  Muscle balance at the knee--moment arms for the normal knee and the ACL-minus knee.

Authors:  W L Buford; F M Ivey; J D Malone; R M Patterson; G L Peare; D K Nguyen; A A Stewart
Journal:  IEEE Trans Rehabil Eng       Date:  1997-12

4.  A musculoskeletal model of the knee for evaluating ligament forces during isometric contractions.

Authors:  K B Shelburne; M G Pandy
Journal:  J Biomech       Date:  1997-02       Impact factor: 2.712

5.  A physiologically based criterion of muscle force prediction in locomotion.

Authors:  R D Crowninshield; R A Brand
Journal:  J Biomech       Date:  1981       Impact factor: 2.712

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

Authors:  Donald R Hume; Alessandro Navacchia; Paul J Rullkoetter; Kevin B Shelburne
Journal:  J Biomech       Date:  2019-01-03       Impact factor: 2.712

7.  A model of the lower limb for analysis of human movement.

Authors:  Edith M Arnold; Samuel R Ward; Richard L Lieber; Scott L Delp
Journal:  Ann Biomed Eng       Date:  2009-12-03       Impact factor: 3.934

8.  Evaluation of knee joint muscle forces and tissue stresses-strains during gait in severe OA versus normal subjects.

Authors:  M Adouni; A Shirazi-Adl
Journal:  J Orthop Res       Date:  2013-08-22       Impact factor: 3.494

9.  A dynamic model of the knee and lower limb for simulating rising movements.

Authors:  Kevin B Shelburne; Marcus G Pandy
Journal:  Comput Methods Biomech Biomed Engin       Date:  2002-04       Impact factor: 1.763

10.  Standardized loads acting in knee implants.

Authors:  Georg Bergmann; Alwina Bender; Friedmar Graichen; Jörn Dymke; Antonius Rohlmann; Adam Trepczynski; Markus O Heller; Ines Kutzner
Journal:  PLoS One       Date:  2014-01-23       Impact factor: 3.240

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  1 in total

1.  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

  1 in total

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