Abstract
A motion-based Inverse Kinematics Knee (IKK) model was developed for Total Knee Replacement (TKR) joints. By tracking a sequence of passive knee motion, the IKK model estimated ligament properties such as insertion locations. The formulation of the IKK model embedded a Forward Kinematics Knee (FKK) [1] model in a numerical optimization algorithm known as the Unscented Kalman Filter [2]. Simulation results performed on a semi-constrained TKR design suggested that ligament insertions could be accurately estimated in the medial-lateral (ML) and the proximal-distal (PD) directions, but less reliably in the anterior-posterior (AP) direction for the tibial component. However, the forward kinematics produced by both the true and estimated ligament properties were nearly identical, suggesting that the IKK model recovered a kinematically equivalent set of ligament properties. These results imply that it may not be necessary to use a patient-specific CT or MRI scan to locate ligaments, which considerably widens potential applications of kinematic-based total knee replacement.
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© 2006 Springer-Verlag Berlin Heidelberg
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Chen, E.C.S., Ellis, R.E. (2006). An Inverse Kinematics Model For Post-operative Knee. In: Larsen, R., Nielsen, M., Sporring, J. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006. MICCAI 2006. Lecture Notes in Computer Science, vol 4190. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11866565_39
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DOI: https://doi.org/10.1007/11866565_39
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