Literature DB >> 24866570

Probabilistic evaluation of predicted force sensitivity to muscle attachment and glenohumeral stability uncertainty.

Jaclyn N Chopp-Hurley1, Joseph E Langenderfer, Clark R Dickerson.   

Abstract

A major benefit of computational modeling in biomechanics research is its ability to estimate internal muscular demands given limited input information. However, several assumptions regarding model parameters and constraints may influence model outputs. This research evaluated the influence of model parameter variability, specifically muscle attachment locations and glenohumeral stability thresholds, on predicted rotator cuff muscle force during internal and external axial humeral rotation tasks. Additionally, relative sensitivity factors assessed which parameters were more contributory to output variability. Modest model parameter variation resulted in considerable variability in predicted force, with origin-insertion locations being particularly influential. Specifically, the scapula attachment site of the subscapularis muscle was important for modulating predicted force, with sensitivity factors ranging from α=0.2 to 0.7 in a neutral position. The largest variability in predicted forces was present for the subscapularis muscle, with average differences of 33.0±9.6% of normalized muscle force (1-99% CI), and a maximal difference of 51% in neutral exertions. Infraspinatus and supraspinatus muscles elicited maximal differences of 15.0 and 20.6%, respectively, between confidence limits. Overall, origin and insertion locations were most influential and thus incorporating geometric variation in the prediction of rotator cuff muscle forces may provide more representative population estimates.

Mesh:

Year:  2014        PMID: 24866570     DOI: 10.1007/s10439-014-1035-3

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  4 in total

1.  Gaussian Process Autoregression for Joint Angle Prediction Based on sEMG Signals.

Authors:  Jie Liang; Zhengyi Shi; Feifei Zhu; Wenxin Chen; Xin Chen; Yurong Li
Journal:  Front Public Health       Date:  2021-05-21

2.  Using a Bayesian Network to Predict L5/S1 Spinal Compression Force from Posture, Hand Load, Anthropometry, and Disc Injury Status.

Authors:  Richard E Hughes
Journal:  Appl Bionics Biomech       Date:  2017-10-01       Impact factor: 1.781

3.  Morphometric analysis of vastus medialis oblique muscle and its influence on anterior knee pain.

Authors:  Marwa M El Sawy; Dalia M E El Mikkawy; Sayed M El-Sayed; Ahmed M Desouky
Journal:  Anat Cell Biol       Date:  2021-03-31

4.  Structure, function, and control of the human musculoskeletal network.

Authors:  Andrew C Murphy; Sarah F Muldoon; David Baker; Adam Lastowka; Brittany Bennett; Muzhi Yang; Danielle S Bassett
Journal:  PLoS Biol       Date:  2018-01-18       Impact factor: 8.029

  4 in total

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