Abstract
The goals of this work were to (i) establish a method for building subject-specific biomechanical models from medical image data, (ii) construct a subject-specific model of the elbow, and (iii) quantify the accuracy of soft tissue excursions estimated from the model. We developed a kinematic model of the elbow joint and its surrounding musculature from magnetic resonance images of a 6′4′’ male cadaver specimen in one limb position. Moment arms estimated from the model (i.e., the changes in muscle-tendon lengths with elbow flexion angle) were compared to moment arms measured experimentally from the same specimen. In five of the six muscles studied, the model explained 84%–94% of the variation in the experimental data. Model estimates of peak elbow flexion moment arm were within 13% of the experimental peaks. Our results suggest that subject-specific musculoskeletal models derived from medical image data have the potential to substantially improve estimates of soft tissue excursions in living subjects.
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© 1998 Springer-Verlag Berlin Heidelberg
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Murray, W.M., Arnold, A.S., Salinas, S., Durbhakula, M.M., Buchanan, T.S., Delp, S.L. (1998). Building biomechanical models based on medical image data: An assessment of model accuracy. In: Wells, W.M., Colchester, A., Delp, S. (eds) Medical Image Computing and Computer-Assisted Intervention — MICCAI’98. MICCAI 1998. Lecture Notes in Computer Science, vol 1496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0056239
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DOI: https://doi.org/10.1007/BFb0056239
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