François Chung, Ph.D.

INRIA project @Aalborg, Denmark (2009). Computer models and simulations of the musculoskeletal system are widely used to study the mechanisms behind human gait and its disorders. To create musculoskeletal models, the common method consists in using a generic model based on data derived from anatomical and biomechanical studies of cadaveric specimens. To adapt this generic model to a specific subject, the usual method consists in scaling it.

However, this scaling introduces errors because it does not account for anatomical differences between subjects. To resolve this issue, we propose a novel semi-automatic method to create subject-specific musculoskeletal models from Magnetic Resonance (MR) images and motion capture data.

First, an accurate modeling of the anatomy is produced using subject-specific medical data and a model-based automatic segmentation. Then, the anatomical model is coupled with motion capture data, joint kinematic information and muscle-tendon actuators to create a subject-specific musculoskeletal model.

This work is a collaboration between:

• EPFL - École Polytechnique Fédérale de Lausanne (CH);
• INRIA Sophia-Antipolis - Institut National de Recherche en Informatique et en Automatique (FR);
• UNIGE - Université de Genève (CH).

The created musculoskeletal models can be used with any motion capture data to produce a specific simulation. The versatility of the framework is one of its qualities as it is not necessary anymore to rely on a standardized musculoskeletal model based on a healthy subject. It should be hence possible to simulate patients with disabilities as long as the acquired data reflect their pathology.

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