Computational Modelling Of Knee Tissue Mechanics During Single Leg Jump Landing

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Computational Modelling of Knee Tissue Mechanics During Single-Leg Jump Landing

Computational Modelling of Knee Tissue Mechanics During Single-Leg Jump Landing
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Book Synopsis Computational Modelling of Knee Tissue Mechanics During Single-Leg Jump Landing by : Harish Rao

Download or read book Computational Modelling of Knee Tissue Mechanics During Single-Leg Jump Landing written by Harish Rao and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The anterior cruciate ligament (ACL) plays a crucial role in stabilising the knee joint in anterior tibial translation and internal tibial rotation. Non-contact ACL injuries are a major concern in sport-related activities due to sudden dynamic manoeuvres involved. Concomitant injuries to other tissues of the knee joint such as meniscal tears are common with ACL injuries. Treatment of ACL injuries through surgical reconstructions and rehabilitation imposes a large socioeconomic burden on healthcare systems. Researchers have extensively used a combination of in-vitro experiments on cadaveric specimens and computational modelling to explore the biomechanical factors surrounding ACL injury in dynamic knee movements. The primary objective of this study was to develop a subject-specific knee finite element (FE) model to simulate an injury-causing motion - single-leg jump landing and validate ACL strain based on previous in-vitro experiments. Medical images of a cadaver specimen were segmented to generate three-dimensional (3D) models of the anatomic structures of the knee joint. High-quality meshes of the segmented 3D models were produced. Digitization technique was used to replicate the knee ligament insertion sites of the cadaver specimen in the model accurately. The kinematic response of the model under basic knee motions was validated with published experimental data. Muscle forces and kinematic inputs from a previous study involving the motion capture of ten participants were used as the boundary conditions to simulate a jump landing motion. Explicit FE analyses were performed on the model under half, and full muscle force conditions and the ACL and meniscal strain outputs were compared with experimental results. Results showed that the ACL strain trends in the half muscle force jump simulations of two participant profiles (P5, P6) agreed well with the in-vitro experimental results from the cadaver knee. However, the computational peak ACL strain values of the two profiles (5.5 % at 228 ms and 4.9 % at 177 ms) did not agree well with the experimental results (2.8 % at 151 ms and 3.5 % at 164 ms). The ACL strain trends during the full muscle force jump simulations of ten participant profiles (P1 - P10) showed better agreement with the experimental results from different cadaver knees of a previous study. In addition, in the half muscle force jump simulations of two participant profiles (P5, P6), the peak values of posterior medial meniscal strain from the FE model (0.7 % and 1.4 %) agreed well with the experimental results (0.75 % and 1.3 %) from different cadaver knees. This study demonstrated a methodology to develop a subject-specific FE model of the knee joint that could be used to recreate in-vitro dynamic experimental conditions to make predictions of ACL and medial meniscal strains, providing an effective approach to overcome the limitations of experimental testing. Future work will use the established model to predict the risk of injury and design injury prevention strategies in dynamic knee loading scenarios.


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