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The First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, 2006. BioRob 2006.
We address the problem of knee pathology assessment by using screw theory to describe the knee motion and by using the screw representation of the motion as an input to a machine learning classifier. The flexions of knees with different pathologies are tracked using an optical tracking system. The screw parameters which describe the transformation of the tibia with respect to the femur in each two successive observation are represented as the instantaneous screw axis of the motion given in itsdoi:10.1109/biorob.2006.1639230 fatcat:sd7j6ra6qnad7icmd6e6nyk57i