Effects of motion segment simulation and joint positioning on spinal loads in trunk musculoskeletal models

Ghezelbash, Farshid; Eskandari, Amir Hossein; Shirazi‐Adl, A.; Arjmand, Navid; El-Ouaaid, Z.; Plamondon, André

doi:10.1016/j.jbiomech.2017.07.014

Cited by 35 publications

(19 citation statements)

References 43 publications

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“…In finite element studies, the complex structures of discs, ligaments and facet joints can be explicitly modelled in detail (Dehghan-Hamani et al, 2019;Khoddam-Khorasani et al, 2018), thereby enabling accurate kinetics analysis in various conditions. Nonetheless, the computational burden is significant (Ghezelbash et al, 2018). In contrast, musculoskeletal simulations using rigidbody models (representing the skeletal system) is another feasible option allowing spine kinematics and kinetics analysis.…”

Section: Introductionmentioning

confidence: 99%

“…State of the art rigid body models of the thoracolumbar spine fail to properly represent the high nonlinearity of FSU stiffness -with stiffness values usually being small for minor FSU displacements (thus inducing small passive forces) but with stiffness typically rapidly increasing with increasing displacement (Izzo et al, 2013) -thereby allowing small active muscle effort near the neutral posture while ensuring stability at the movement extremes. In finite element models, nonlinear stiffness is usually incorporated using detailed passive structures or nonlinear deformable beams (Ghezelbash et al, 2018). For rigid-body models, only a few nonlinear stiffness expressions were proposed previously and these were either only for one single FSU (Malakoutian et al, 2016;Weisse et al, 2012), for explicitly modelled ligaments (Liu et al, 2019;Liu et al, 2018) or had not been assessed comprehensively (Cholewicki et al, 1996).…”

Section: Introductionmentioning

confidence: 99%

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Implementation of physiological functional spinal units in a rigid-body model of the thoracolumbar spine

Wang

Groote

et al. 2020

Journal of Biomechanics

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Most of the current rigid-body models of the complete thoracolumbar spine do not properly model the intervertebral joint as the highly nonlinear stiffness is not incorporated comprehensively and the effects of compressive load on stiffness is commonly being neglected. Based on published in vitro data of individual intervertebral joint flexibility, multi-level six degree-of-freedom nonlinear stiffness of functional spinal units was modelled and incorporated in a rigid-body model of the thoracolumbar spine. To estimate physiological in vivo conditions of the entire spine, stiffening effects caused by directly applied compressive loads, and contributions to mono-segmental stiffness from the rib cage as well as multi-segmental interactions in the thoracic spine were analysed and implemented. Forward dynamic simulations were performed to simulate in vitro tests that measured the load-displacement response of the spine under various loading conditions. The predicted kinematic responses of the model were in agreement with in vitro measurements, with correlations between simulated and measured segmental displacements varying between 0.66 and 0.97 (p < 0.05) and average deviations below 1:6°. Coupling relationships were found between lateral bending and axial rotation. Under compressive loads, the model behaved stiffer and showed a decreased range of motion: The flexion/extension response of the full thoracolumbar spine under compressive loads up to 800 N was found to strongly correlate with the literature (r = 0.99, p < 0.0001). The implementation of physiological functional spinal units with nonlinear stiffness properties into rigid-body models can enhance accuracy of biomechanical simulations, and enable detailed analysis of spinal kinematics under complex loading conditions seen in vivo.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Implementation of physiological functional spinal units in a rigid-body model of the thoracolumbar spine

Wang

Groote

et al. 2020

Journal of Biomechanics

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“…Both optimization‐ and EMG‐driven MS models routinely simulate intervertebral joints by spherical joints or deformable beams, a simplification that, apart from errors involved depending on the model used, prevents these models from the evaluation of internal stresses and any estimates of detailed load sharing among various joint passive structures. To resolve this latter shortcoming, we have recently developed a novel hybrid model in which the estimated trunk muscle forces from a MS model are input to a geometrically‐detailed passive finite element (FE) model to estimate joint response (facet joint forces [FJFs], ligament forces, stresses‐strains in disc annulus, and IDP).…”

Section: Introductionmentioning

confidence: 99%

Subject‐specific loads on the lumbar spine in detailed finite element models scaled geometrically and kinematic‐driven by radiography images

Dehghan-Hamani

Arjmand

Shirazi‐Adl

2019

Numer Methods Biomed Eng

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Traditional load‐control musculoskeletal and finite element (FE) models of the spine fail to accurately predict in vivo intervertebral joint loads due mainly to the simplifications and assumptions when estimating redundant trunk muscle forces. An alternative powerful protocol that bypasses the calculation of muscle forces is to drive the detailed FE models by image‐based in vivo displacements. Development of subject‐specific models, however, both involves the risk of extensive radiation exposures while imaging in supine and upright postures and is time consuming in terms of the reconstruction of the vertebrae, discs, ligaments, and facets geometries. This study therefore aimed to introduce a remedy for the development of subject‐specific FE models by scaling the geometry of an existing detailed FE model of the T12‐S1 lumbar spine. Five subject‐specific scaled models were driven by their own radiography image‐based displacements in order to predict joint loads, ligament forces, facet joint forces, and disc fiber strains during relaxed upright as well as moderate flexion and extension tasks. The predicted intradiscal pressures were found in adequate agreement with in vivo data for upright, flexion, and extension tasks. There were however large intersubject variations in the estimated joint loads and facet forces.

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“…Thirdly, we did not incorporate spinal ligaments but implemented their collective rotational stiffnesses linearly in the intervertebral and rib cage joints. Thus, excluding the ligaments or simplifying their non-linear mechanical behaviors could alter the load sharing mechanism between the muscles and affect our findings (Putzer, Auer, et al 2016;Ghezelbash et al 2018). For example, Putzer, Auer, et al (2016) found that implementing stiffer ligaments could cause a shift of the loads to the lower lumbar disc levels.…”

Section: Discussionmentioning

confidence: 93%

Sensitivity of muscle and intervertebral disc force computations to variations in muscle attachment sites

Bayoğlu

Güldeniz

Koopman

et al. 2019

Computer Methods in Biomechanics and Biomedical Engineering

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The current paper aims at assessing the sensitivity of muscle and intervertebral disc force computations against potential errors in modeling muscle attachment sites. We perturbed each attachment location in a complete and coherent musculoskeletal model of the human spine and quantified the changes in muscle and disc forces during standing upright, flexion, lateral bending, and axial rotation of the trunk. Although the majority of the muscles caused minor changes (less than 5%) in the disc forces, certain muscle groups, for example, quadratus lumborum, altered the shear and compressive forces as high as 353% and 17%, respectively. Furthermore, percent changes were higher in the shear forces than in the compressive forces. Our analyses identified certain muscles in the rib cage (intercostales interni and intercostales externi) and lumbar spine (quadratus lumborum and longissimus thoracis) as being more influential for computing muscle and disc forces. Furthermore, the disc forces at the L4/L5 joint were the most sensitive against muscle attachment sites, followed by T6/T7 and T12/L1 joints. Presented findings suggest that modeling muscle attachment sites based on solely anatomical illustrations might lead to erroneous evaluation of internal forces and promote using anatomical datasets where these locations were accurately measured. When developing a personalized model of the spine, certain care should also be paid especially for the muscles indicated in this work.

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Effects of motion segment simulation and joint positioning on spinal loads in trunk musculoskeletal models

Cited by 35 publications

References 43 publications

Implementation of physiological functional spinal units in a rigid-body model of the thoracolumbar spine

Implementation of physiological functional spinal units in a rigid-body model of the thoracolumbar spine

Subject‐specific loads on the lumbar spine in detailed finite element models scaled geometrically and kinematic‐driven by radiography images

Sensitivity of muscle and intervertebral disc force computations to variations in muscle attachment sites

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