Validation of a Finite Element Simulation for Predicting Individual Knee Joint Kinematics

Goal: We introduce an in-vivo validated finite element (FE) simulation approach for predicting individual knee joint kinematics. Our vision is to improve clinicians' understanding of the complex individual anatomy and potential pathologies to improve treatment and restore physiological joint ki...

Full description

Saved in:
Bibliographic Details
Published inIEEE open journal of engineering in medicine and biology Vol. 5; pp. 125 - 132
Main Authors Theilen, Elin, Rorich, Anna, Lange, Thomas, Bendak, Sebastian, Huber, Cora, Schmal, Hagen, Izadpanah, Kaywan, Georgii, Joachim
Format Journal Article
LanguageEnglish
Published United States IEEE 01.01.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Goal: We introduce an in-vivo validated finite element (FE) simulation approach for predicting individual knee joint kinematics. Our vision is to improve clinicians' understanding of the complex individual anatomy and potential pathologies to improve treatment and restore physiological joint kinematics. Methods: Our 3D FE modeling approach for individual human knee joints is based on segmentation of anatomical structures extracted from routine static magnetic resonance (MR) images. We validate the predictive abilities of our model using static MR images of the knees of eleven healthy volunteers in dedicated knee poses, which are achieved using a customized MR-compatible pneumatic loading device. Results: Our FE simulations reach an average translational accuracy of 2 mm and an average angular accuracy of 1<inline-formula><tex-math notation="LaTeX">^\circ</tex-math></inline-formula> compared to the reference knee pose. Conclusions: Reaching high accuracy, our individual FE model can be used in the decision-making process to restore knee joint stability and functionality after various knee injuries.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:2644-1276
2644-1276
DOI:10.1109/OJEMB.2023.3258362