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This Article Full Text Full Text (PDF) All Versions of this Article: 91/2/371    most recent expphysiol.2005.031047v1 Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Fernandez, J. W. Articles by Pandy, M. G. Search for Related Content PubMed PubMed Citation Articles by Fernandez, J. W. Articles by Pandy, M. G.

¹ Department of Mechanical and Manufacturing Engineering, The University of Melbourne, Victoria 3010, Australia² Department of Biomedical Engineering, The University of Texas at Austin, 1 University Station, C0800 Austin, TX 78712-0238, USA

Magnetic resonance imaging, bi-plane X-ray fluoroscopy and biomechanical modelling are enabling technologies for the non-invasive evaluation of muscle, ligament and joint function during dynamic activity. This paper reviews these various technologies in the context of their application to the study of human movement. We describe how three-dimensional, subject-specific computer models of the muscles, ligaments, cartilage and bones can be developed from high-resolution magnetic resonance images; how X-ray fluoroscopy can be used to measure the relative movements of the bones at a joint in three dimensions with submillimetre accuracy; how complex 3-D dynamic simulations of movement can be performed using new computational methods based on non-linear control theory; and how musculoskeletal forces derived from such simulations can be used as inputs to elaborate finite-element models of a joint to calculate contact stress distributions on a subject-specific basis. A hierarchical modelling approach is highlighted that links rigid-body models of limb segments with detailed finite-element models of the joints. A framework is proposed that integrates subject-specific musculoskeletal computer models with highly accurate in vivo experimental data.

(Received 28 September 2005; accepted after revision 2 January 2006; first published online 11 January 2006)
Corresponding author J. W. Fernandez: Department of Mechanical and Manufacturing Engineering, The University of Melbourne, Victoria 3010, Australia. Email: justinf{at}unimelb.edu.au

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