scholarly journals Effect of lower-limb joint models on subject-specific musculoskeletal models and simulations of daily motor activities

2015 ◽  
Vol 48 (16) ◽  
pp. 4198-4205 ◽  
Author(s):  
Giordano Valente ◽  
Lorenzo Pitto ◽  
Rita Stagni ◽  
Fulvia Taddei
2017 ◽  
Vol 139 (9) ◽  
Author(s):  
Michael Skipper Andersen ◽  
Mark de Zee ◽  
Michael Damsgaard ◽  
Daniel Nolte ◽  
John Rasmussen

Knowledge of the muscle, ligament, and joint forces is important when planning orthopedic surgeries. Since these quantities cannot be measured in vivo under normal circumstances, the best alternative is to estimate them using musculoskeletal models. These models typically assume idealized joints, which are sufficient for general investigations but insufficient if the joint in focus is far from an idealized joint. The purpose of this study was to provide the mathematical details of a novel musculoskeletal modeling approach, called force-dependent kinematics (FDK), capable of simultaneously computing muscle, ligament, and joint forces as well as internal joint displacements governed by contact surfaces and ligament structures. The method was implemented into the anybody modeling system and used to develop a subject-specific mandible model, which was compared to a point-on-plane (POP) model and validated against joint kinematics measured with a custom-built brace during unloaded emulated chewing, open and close, and protrusion movements. Generally, both joint models estimated the joint kinematics well with the POP model performing slightly better (root-mean-square-deviation (RMSD) of less than 0.75 mm for the POP model and 1.7 mm for the FDK model). However, substantial differences were observed when comparing the estimated joint forces (RMSD up to 24.7 N), demonstrating the dependency on the joint model. Although the presented mandible model still contains room for improvements, this study shows the capabilities of the FDK methodology for creating joint models that take the geometry and joint elasticity into account.


2016 ◽  
Vol 139 (1) ◽  
Author(s):  
Laurent Dumas ◽  
Tamara El Bouti ◽  
Didier Lucor

Cardiovascular diseases are currently the leading cause of mortality in the population of developed countries, due to the constant increase in cardiovascular risk factors, such as high blood pressure, cholesterol, overweight, tobacco use, lack of physical activity, etc. Numerous prospective and retrospective studies have shown that arterial stiffening is a relevant predictor of these diseases. Unfortunately, the arterial stiffness distribution across the human body is difficult to measure experimentally. We propose a numerical approach to determine the arterial stiffness distribution of an arterial network using a subject-specific one-dimensional model. The proposed approach calibrates the optimal parameters of the reduced-order model, including the arterial stiffness, by solving an inverse problem associated with the noninvasive in vivo measurements. An uncertainty quantification analysis has also been carried out to measure the contribution of the model input parameters variability, alone or by interaction with other inputs, to the variation of clinically relevant hemodynamic indices, here the arterial pulse pressure. The results obtained for a lower limb model, demonstrate that the numerical approach presented here can provide a robust and subject-specific tool to the practitioner, allowing an early and reliable diagnosis of cardiovascular diseases based on a noninvasive clinical examination.


2018 ◽  
Author(s):  
Edin K. Suwarganda ◽  
Laura E. Diamond ◽  
David J. Saxby ◽  
David G. Lloyd ◽  
A. Killen Bryce ◽  
...  

AbstractAccurate representation of subject-specific bone anatomy in lower-limb musculoskeletal models is important for human movement analyses and simulations. Mathematical methods can reconstruct geometric bone models using incomplete imaging of bone by morphing bone model templates, but the validity of these methods has not been fully explored. The purpose of this study was to determine the minimal imaging requirements for accurate reconstruction of geometric bone models. Complete geometric pelvis and femur models of 14 healthy adults were reconstructed from magnetic resonance imaging through segmentation. From each complete bone segmentation, three sets of incomplete segmentations (set 1 being the most incomplete) were created to test the effect of imaging incompleteness on reconstruction accuracy. Geometric bone models were reconstructed from complete sets, three incomplete sets, and two motion capture-based methods. Reconstructions from (in)complete sets were generated using statistical shape modelling, followed by host-mesh and local-mesh fitting through the Musculoskeletal Atlas Project Client. Reconstructions from motion capture-based methods used positional data from skin surface markers placed atop anatomic landmarks and estimated joint centre locations as target points for statistical shape modelling and linear scaling. Accuracy was evaluated with distance error (mm) and overlapping volume similarity (%) between complete bone segmentation and reconstructed bone models, and statistically compared using a repeated measure analysis of variance (p<0.05). Motion capture-based methods produced significantly higher distance error than reconstructions from (in)complete sets. Pelvis volume similarity reduced significantly with the level of incompleteness: complete set (92.70±1.92%), set 3 (85.41±1.99%), set 2 (81.22±3.03%), set 1 (62.30±6.17%), motion capture-based statistical shape modelling (41.18±9.54%), and motion capture-based linear scaling (26.80±7.19%). A similar trend was observed for femur volume similarity. Results indicate that imaging two relevant bone regions produces overlapping volume similarity > 80% compared to complete segmented bone models. These findings have implications for improving movement analysis and simulation with subject-specific musculoskeletal models.


2019 ◽  
Vol 8 (11) ◽  
pp. 509-517 ◽  
Author(s):  
Kyoung-Tak Kang ◽  
Yong-Gon Koh ◽  
Kyoung-Mi Park ◽  
Chong-Hyuck Choi ◽  
Min Jung ◽  
...  

Objectives The aim of this study was to investigate the biomechanical effect of the anterolateral ligament (ALL), anterior cruciate ligament (ACL), or both ALL and ACL on kinematics under dynamic loading conditions using dynamic simulation subject-specific knee models. Methods Five subject-specific musculoskeletal models were validated with computationally predicted muscle activation, electromyography data, and previous experimental data to analyze effects of the ALL and ACL on knee kinematics under gait and squat loading conditions. Results Anterior translation (AT) significantly increased with deficiency of the ACL, ALL, or both structures under gait cycle loading. Internal rotation (IR) significantly increased with deficiency of both the ACL and ALL under gait and squat loading conditions. However, the deficiency of ALL was not significant in the increase of AT, but it was significant in the increase of IR under the squat loading condition. Conclusion The results of this study confirm that the ALL is an important lateral knee structure for knee joint stability. The ALL is a secondary stabilizer relative to the ACL under simulated gait and squat loading conditions. Cite this article: Bone Joint Res 2019;8:509–517.


2020 ◽  
Vol 17 (2) ◽  
pp. 026029 ◽  
Author(s):  
Dharmendra Gurve ◽  
Denis Delisle-Rodriguez ◽  
Maria Romero-Laiseca ◽  
Vivianne Cardoso ◽  
Flavia Loterio ◽  
...  

2017 ◽  
Vol 54 ◽  
pp. 80-87 ◽  
Author(s):  
Michael D. Harris ◽  
Bruce A. MacWilliams ◽  
K. Bo Foreman ◽  
Christopher L. Peters ◽  
Jeffrey A. Weiss ◽  
...  

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