Comparison the Performance of Rajagopal Musculoskeletal Model and its Updated Versions in Prediction of the Knee Joint Contact Forces During Walking and Squatting

Authors

1 Mechanical engineering department Faculty of engineering Birjand university Birjand Iran

2 Prof., Mech. Eng., ETH Zurich, Zurich, Switzerland.

3 Ph.D., Mech. Eng., ETH Zurich, Zurich, Switzerland.

4 Faculty of Engineering, University of Birjand, Birjand, Iran

Abstract

Musculoskeletal models are powerful and practical tools to estimate internal body loads non-invasively. Although they are accurate enough for gait activities, large errors have been seen for activities with deep hip and knee flexion angles. Recently two studies have updated one of the existing powerful models (Rajagopal) and proposed new models for pedaling (Lai) and deep squatting (Catelli). This study compares these three models during level walking and squatting using the CAMS-Knee datasets and OpenSim software. For level walking, there was generally good agreement between all models in predicted muscle activations and EMG signals. There are low discrepancies in predicted KCFs by different models and in-vivo data (average error <20%). For squatting, muscle activation patterns have significant differences in various models and they showed considerably larger discrepancies from the EMG measurements. Our study found average peak KCF errors of 60% for Catelli, 72% for Lai, and 83% for the Rajagopal model. Although the errors are reduced in updated models, they still represent high errors that indicate the inadequacy of changes made in these models.

Keywords

References

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Journal of Solid and Fluid Mechanics
Volume 11, Issue 5
November and December 2021
Pages 83-94

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