Prediction of medial and lateral contact force of the knee joint during normal and turning gait after total knee replacement

Abstract

The computational modeling approach has commonly been used to predict knee joint contact forces, muscle forces, and ligament loads during activities of daily living. Knowledge of these forces has several potential applications, for example, within design of equipment to protect the knee joint from injury and to plan adequate rehabilitation protocols, although clinical applications of computational models are still evolving and one of the limiting factors is model validation. The objective of this study was to extend previous modeling technique and to improve the validity of the model prediction using publicly available data set of the fifth “Grand Challenge Competition to Predict In Vivo Knee Loads.” A two-stage modeling approach, which combines conventional inverse dynamic analysis (the first stage) with a multi-body subject-specific lower limb model (the second stage), was used to calculate medial and lateral compartment contact forces. The validation was performed by direct comparison of model predictions and experimental measurement of medial and lateral compartment contact forces during normal and turning gait. The model predictions of both medial and lateral contact forces showed strong correlations with experimental measurements in normal gait (r = 0.75 and 0.71) and in turning gait trials (r = 0.86 and 0.72), even though the current technique over-estimated medial compartment contact forces in swing phase. The correlation coefficient, Sprague and Geers metrics, and root mean squared error indicated that the lateral contact forces were predicted better than medial contact forces in comparison with the experimental measurements during both normal and turning gait trials.