Musculoskeletal simulation model generation from MRI datasets and motion capture data

Abstract Today computer models and computer simulations of the muscu-loskeletal system are widely used to study the mechanisms behind human gait and its disorders. The common way of creating musculoskeletal models is to use a ge-neric musculoskeletal model based on data derived from anatomical and biome-chanical studies of cadaverous specimens. To adapt this generic model to a spe-cific subject, the usual approach is to scale it. This scaling has been reported to introduce several errors because it does not always account for subject-specific anatomical differences. As a result, a novel semi-automatic workflow is proposed that creates subject-specific musculoskeletal models from Magnetic Resonance Imaging (MRI) datasets and motion capture data. Based on subject-specific medi-cal data and a model-based automatic segmentation approach, an accurate model-ing of the anatomy can be produced while avoiding the scaling operation. This anatomical model coupled with motion capture data, joint kinematics information and muscle-tendons actuators is finally used to create a subject-specific muscu-loskeletal model