title: Fine tuning total knee replacement contact force prediction algorithms using blinded model validation.
abstract: 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.
authors: Department of Orthopedic Surgery, Rush University Medical Center, 1611 West Harrison, Chicago, IL 60612, USA. Hannah_Lundberg@rush.edu
authors: Hannah J
authors: HJ
authors: Lundberg
authors: Christopher
authors: C
authors: Knowlton
authors: Markus A
authors: MA
authors: Wimmer
mesh_terms: D000369:Aged, 80 and over; D000465:Algorithms; D019645:Arthroplasty, Replacement, Knee; D001696:Biomechanical Phenomena; D005684:Gait / Q000502:physiology; D006801:Humans; D008297:Male; D055595:Mechanical Phenomena; D008954:Models, Biological; D016138:Walking / Q000502:physiology