Literature DB >> 28327299

Subject-specific musculoskeletal modeling in the evaluation of shoulder muscle and joint function.

Wen Wu1, Peter V S Lee1, Adam L Bryant1, Mary Galea1, David C Ackland2.   

Abstract

Upper limb muscle force estimation using Hill-type muscle models depends on musculotendon parameter values, which cannot be readily measured non-invasively. Generic and scaled-generic parameters may be quickly and easily employed, but these approaches do not account for an individual subject's joint torque capacity. The objective of the present study was to develop a subject-specific experimental testing and modeling framework to evaluate shoulder muscle and joint function during activities of daily living, and to assess the capacity of generic and scaled-generic musculotendon parameters to predict muscle and joint function. Three-dimensional musculoskeletal models of the shoulders of 6 healthy subjects were developed to calculate muscle and glenohumeral joint loading during abduction, flexion, horizontal flexion, nose touching and reaching using subject-specific, scaled-generic and generic musculotendon parameters. Muscle and glenohumeral joint forces calculated using generic and scaled-generic models were significantly different to those of subject-specific models (p<0.05), and task dependent; however, scaled-generic model calculations of shoulder glenohumeral joint force demonstrated better agreement with those of subject-specific models during abduction and flexion. Muscles in generic musculoskeletal models operated further from the plateau of their force-length curves than those of scaled-generic and subject-specific models, while muscles in subject-specific models operated over a wider region of their force length curves than those of the generic or scaled-generic models, reflecting diversity of subject shoulder strength. The findings of this study suggest that generic and scaled-generic musculotendon parameters may not provide sufficient accuracy in prediction of shoulder muscle and joint loading when compared to models that employ subject-specific parameter-estimation approaches. Copyright Â
© 2016 Elsevier Ltd. All rights reserved.

Keywords:  Biomechanical model; Glenohumeral; Musculotendon parameters; Upper limb

Mesh:

Year:  2016        PMID: 28327299     DOI: 10.1016/j.jbiomech.2016.09.025

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


  7 in total

1.  The moment arms of the muscles spanning the glenohumeral joint: a systematic review.

Authors:  Freya Hik; David C Ackland
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2.  Statistical Quantification of the Effects of Marker Misplacement and Soft-Tissue Artifact on Shoulder Kinematics and Kinetics.

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Review 3.  A review of musculoskeletal modelling of human locomotion.

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Journal:  Interface Focus       Date:  2021-08-13       Impact factor: 4.661

4.  In vivo human lower limb muscle architecture dataset obtained using diffusion tensor imaging.

Authors:  James P Charles; Felipe Suntaxi; William J Anderst
Journal:  PLoS One       Date:  2019-10-15       Impact factor: 3.240

5.  Three-Dimensional Upper Body Kinematics and Inter-articular Kinematic Sequence During a Canoe Polo Throw.

Authors:  Najoua Assila; Cyril Delavallade; Yoann Blache; Christian Berger-Vachon; Philippe Collotte; Sonia Duprey
Journal:  Front Sports Act Living       Date:  2021-12-15

6.  A Matlab toolbox for scaled-generic modeling of shoulder and elbow.

Authors:  Ehsan Sarshari; Yasmine Boulanaache; Alexandre Terrier; Alain Farron; Philippe Mullhaupt; Dominique Pioletti
Journal:  Sci Rep       Date:  2021-10-21       Impact factor: 4.379

7.  Evaluating the effects of arthroscopic Bankart repair and open Latarjet shoulder stabilisation procedures on shoulder joint neuromechanics and function: a single-centre, parallel-arm trial protocol.

Authors:  Aaron Fox; Jason Bonacci; Stephen D Gill; Richard S Page
Journal:  BMJ Open Sport Exerc Med       Date:  2021-02-23
  7 in total

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