Research Papers

Verification of Predicted Knee Replacement Kinematics During Simulated Gait in the Kansas Knee Simulator

[+] Author and Article Information
Jason P. Halloran

Department of Mechanical and Materials Engineering, Computational Biomechanics Laboratory, University of Denver, 2390 South York, Denver, CO 80208

Chadd W. Clary, Lorin P. Maletsky

Department of Mechanical Engineering, University of Kansas, 1530 W 15th Street, Lawrence, KS 66045

Mark Taylor

Bioengineering Sciences Research Group, University of Southampton, Southampton SO17 1BJ, UK

Anthony J. Petrella

 DePuy, a Johnson & Johnson Company, 700 Orthopaedic Drive, Warsaw, IN 46581

Paul J. Rullkoetter1

Department of Mechanical and Materials Engineering, Computational Biomechanics Laboratory, University of Denver, 2390 South York, Denver, CO 80208prullkoe@du.edu


Corresponding author.

J Biomech Eng 132(8), 081010 (Jul 01, 2010) (6 pages) doi:10.1115/1.4001678 History: Received September 25, 2006; Revised April 06, 2010; Posted April 28, 2010; Published July 01, 2010; Online July 01, 2010

Evaluating total knee replacement kinematics and contact pressure distributions is an important element of preclinical assessment of implant designs. Although physical testing is essential in the evaluation process, validated computational models can augment these experiments and efficiently evaluate perturbations of the design or surgical variables. The objective of the present study was to perform an initial kinematic verification of a dynamic finite element model of the Kansas knee simulator by comparing predicted tibio- and patellofemoral kinematics with experimental measurements during force-controlled gait simulation. A current semiconstrained, cruciate-retaining, fixed-bearing implant mounted in aluminum fixtures was utilized. An explicit finite element model of the simulator was developed from measured physical properties of the machine, and loading conditions were created from the measured experimental feedback data. The explicit finite element model allows both rigid body and fully deformable solutions to be chosen based on the application of interest. Six degrees-of-freedom kinematics were compared for both tibio- and patellofemoral joints during gait loading, with an average root mean square (rms) translational error of 1.1 mm and rotational rms error of 1.3 deg. Model sensitivity to interface friction and damping present in the experimental joints was also evaluated and served as a secondary goal of this paper. Modifying the metal-polyethylene coefficient of friction from 0.1 to 0.01 varied the patellar flexion-extension and tibiofemoral anterior-posterior predictions by 7 deg and 2 mm, respectively, while other kinematic outputs were largely insensitive.

Copyright © 2010 by American Society of Mechanical Engineers
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Figure 1

Experimental Kansas knee simulator (left) and finite element representation with implant mesh (right). Applied loads and flexion angle are represented by arrows. Boundary conditions include the axial load, hip flexion angle, quadriceps load, internal-external torque, and adduction-abduction force.

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Figure 2

Applied loading and flexion angle as a function of the gait cycle. 0–60% gait cycle represents stance phase (0% equals heal strike) and 60–100% gait cycle represents the swing phase. The same is true for all figures with percent gait cycle on the abscissa.

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Figure 3

Model and experimental tibiofemoral flexion (+)-extension (F-E) and varus (+)-valgus (V-V) rotations as a function of the gait cycle. The results represent a coefficient of friction of 0.08, and the experimental results represent 8 averaged cycles.

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Figure 4

Experimental and predicted tibiofemoral internal (+)-external (I-E) rotation as a function of the gait cycle. Data include rigid body analyses with zero and nominal ankle dampings, as well as a deformable analysis with nominal ankle damping (all results are with a coefficient of friction of 0.08).

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Figure 5

Tibiofemoral anterior (-)-posterior (A-P) experimental and model-predicted displacement as a function of the gait cycle. Plotted data include rigid body analysis with various friction values, and a deformable analysis with a coefficient of friction=0.08 (tibio- and patellofemoral). Very close agreement between the rigid body and deformable analyses allow the results to be representative of either analysis for the presented coefficient values.

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Figure 6

Model and experimental patellofemoral rotations as a function of the gait cycle (+ rotations are extension, internal tilt, and varus spin; all results are with a coefficient of friction of 0.08)

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Figure 7

Experimental and model-predicted patellofemoral flexion (-)-extension as a function of the gait cycle using selected coefficient of friction values

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Figure 8

Experimental and model-predicted patellofemoral translations as a function of the gait cycle (+ translations are superior, anterior, and lateral)



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