An inverse kinematics model for post-operative knee. Ligament parameters estimation from knee motion.
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) model in a numerical optimization algorithm known as the Unscented Kalman Filter. 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.
Chen
Elvis C S
EC
School of Computing, Queen's University, Canada. chene@cs.queensu.ca
Ellis
Randy E
RE
D001696:Biomechanical Phenomena / Q000379:methods*; D003198:Computer Simulation; D004548:Elasticity; D006801:Humans; D007719:Knee Joint / Q000502:physiology* / Q000601:surgery*; D008022:Ligaments / Q000502:physiology* / Q000601:surgery*; D008954:Models, Biological; D009068:Movement / Q000502:physiology; D011184:Postoperative Period; D016059:Range of Motion, Articular / Q000502:physiology*; D013314:Stress, Mechanical