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An Inverse Kinematics Model For Post-operative Knee

  • Elvis C. S. Chen
  • Randy E. Ellis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4190)

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.

Keywords

Total Knee Replacement Tibial Component Unscented Kalman Filter Kinematics Knee Knee Motion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Elvis C. S. Chen
    • 1
  • Randy E. Ellis
    • 1
    • 2
  1. 1.School of ComputingQueen’s UniversityCanada
  2. 2.Brigham and Women’s HospitalHarvardU.S.A.

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