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Research Papers

Fine Tuning Total Knee Replacement Contact Force Prediction Algorithms Using Blinded Model Validation

[+] Author and Article Information
Hannah J. Lundberg

Department of Orthopedic Surgery,
Rush University Medical Center,
1611 West Harrison,
Suite 201 Chicago, IL 60612
e-mail: Hannah_Lundberg@rush.edu

Christopher Knowlton

Department of Orthopedic Surgery,
Rush University Medical Center,
1611 West Harrison,
Suite 201 Chicago, IL 60612;
Department of Bioengineering,
University of Illinois at Chicago,
851 South Morgan Street,
218 SEO Chicago, IL 60607

Markus A. Wimmer

Department of Orthopedic Surgery,
Rush University Medical Center,
1611 West Harrison,
Suite 201 Chicago, IL 60612

1Corresponding author.

Contributed by the Bioengineering Division of ASME for publication in the JOURNAL OF BIOMECHANICAL ENGINEERING. Manuscript received October 22, 2012; final manuscript received January 7, 2013; accepted manuscript posted January 18, 2013; published online February 7, 2013. Editor: Beth Winkelstein.

J Biomech Eng 135(2), 021015 (Feb 07, 2013) (9 pages) Paper No: BIO-12-1506; doi: 10.1115/1.4023388 History: Received October 22, 2012; Revised January 07, 2013; Accepted January 18, 2013

The purpose of this study was to perform a blinded comparison of model predictions of total knee replacement contact forces to in vivo forces from an instrumented prosthesis during normal walking and medial thrust gait by participating in the “Third Grand Challenge Competition to Predict in vivo Knee Loads.” We also evaluated model assumptions that were critical for accurate force predictions. Medial, lateral, and total axial forces through the knee were calculated using a previously developed and validated parametric numerical model. The model uses equilibrium equations between internal and external moments and forces to obtain knee joint contact forces and calculates a range of forces at instances during the gait cycle through parametric variation of muscle activity levels. For 100 instances during a normal over-ground gait cycle, model root mean square differences from eTibia data were 292, 248, and 281 for medial, lateral, and total contact forces, respectively. For 100 instances during a medial thrust gait cycle, model root mean square differences from eTibia data were 332, 234, and 470 for medial, lateral, and total contact forces, respectively. The percent difference between measured and predicted peak total axial force was 2.89% at the first peak and 9.36% at the second peak contact force for normal walking and 3.94% at the first peak and 14.86% at the second peak contact force for medial thrust gait. After unblinding, changes to model assumptions improved medial and lateral force predictions for both gait styles but did not improve total force predictions. Axial forces computed with the model compared well to the eTibia data under blinded and unblinded conditions. Knowledge of detailed knee kinematics, namely anterior-posterior translation, appears to be critical in obtaining accurate force predictions.

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Figures

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Fig. 2

Nine equilibrium equations used to solve for 9 unknowns. Fmedialx, Flateralx, Fmedialy, Flateraly, Fmedialz, and Flateralz are the unknown medial and lateral tibial plateau contact force components. A, B, and C are the unknown muscle group activation levels. D is the activation of passive structures (0 or 1). E is the antagonist activation level. Mexternalx, Mexternaly, and Mexternalz are the external knee joint moments, and Fexternalx, Fexternaly, and Fexternalz are the external knee joint forces. Mix, Miy, and Miz are the maximum physiological muscle moments, and Fix, Fiy, and Fiz are the maximum physiological muscle forces. ai, bi, and ci are the parametrically varied relative muscle activation levels. mamedx, malatx, mamedy, malaty, mamedz, malatz define the location of the contact point from the center of the medial (med) and lateral (lat) tibial plateau. ml_ratio is the ratio of medial to total contact force through the knee. x, y, and z: point laterally, anteriorly, and superiorly, respectively, from the center of the surface of the tibial plateau. Note that in the coordinate system a right-hand rule is used for a right knee and a left-hand rule is used for a left knee where y points in the direction of walking.

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Fig. 1

Gait kinematics and kinetics used as inputs to the parametric model were computed in MotionMonitor for normal and medial thrust gait. Solid lines show the data used in blinded model predictions. Dashed lines show the kinematics that were changed for unblinded model predictions: internal-external (I/E) rotation. and anterior-posterior (A/P) translation for normal gait, and A/P translation for medial thrust gait. Gray areas of the graph represent the swing phase. Note for blinded predictions of medial thrust gait, A/P translation was set to zero throughout the gait cycle. Units for external moments are in percent body weight times height (BW*Ht).

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Fig. 3

Original blinded model predictions of axial force in the medial (dark diamonds) and lateral (light triangles) compartments of the knee compared to the regressed eTibia medial (dark line) and lateral (light line) axial forces for the normal walking and medial thrust gait competition trials. Note different y-axis scales.

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Fig. 4

Unblinded model predictions of axial force in the medial (dark diamonds) and lateral (light triangles) compartments of the knee compared to the regressed eTibia medial (dark line) and lateral (light line) axial forces for five normal walking trials and five medial thrust gait trials. Note different y-axis scales for each gait style.

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Fig. 5

Unblinded model mean predictions (dots) and solution spaces (shaded area) of total axial force compared to the total axial force from eTibia data (line) for five normal walking trials and five medial thrust gait trials. Note different y-axis limits for each gait style.

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