A probabilistic model of glenohumeral external rotation strength for healthy normals and rotator cuff tear cases

Joseph E. Langenderfer, James E. Carpenter, Marjorie E. Johnson, Kai Nan An, Richard E. Hughes

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


The reigning paradigm of musculoskeletal modeling is to construct deterministic models from parameters of an "average" subject and make predictions for muscle forces and joint torques with this model. This approach is limited because it does not perform well for outliers, and it does not model the effects of population parameter variability. The purpose of this study was to simulate variability in musculoskeletal parameters on glenohumeral external rotation strength in healthy normals, and in rotator cuff tear cases using a Monte Carlo model. The goal was to determine if variability in musculoskeletal parameters could quantifiably explain variability in glenohumeral external rotation strength. Multivariate Gamma distributions for musculoskeletal architecture and moment arm were constructed from empirical data. Gamma distributions of measured joint strength were constructed. Parameters were sampled from the distributions and input to the model to predict muscle forces and joint torques. The model predicted measured joint torques for healthy normals, subjects with supraspinatus tears, and subjects with infraspinatus-supraspinatus tears with small error. Muscle forces for the three conditions were predicted and compared. Variability in measured torques can be explained by differences in parameter variability.

Original languageEnglish (US)
Pages (from-to)465-476
Number of pages12
JournalAnnals of Biomedical Engineering
Issue number3
StatePublished - Mar 2006


  • Infraspinatus
  • Monte Carlo
  • Musculoskeletal model
  • Shoulder
  • Stochastic
  • Supraspinatus
  • Teres minor

ASJC Scopus subject areas

  • Biomedical Engineering


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