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在被动弯曲的腰椎中,负载分布在椎体、肌肉、脊柱韧带和椎间盘之间。

Loads distributed in vivo among vertebrae, muscles, spinal ligaments, and intervertebral discs in a passively flexed lumbar spine.

机构信息

Forschungsgesellschaft, für Angewandte Systemsicherheit, und Arbeitsmedizin mbH, Biomechanik & Ergonomie, Lucas-Cranach Platz 2, 99097, Erfurt, Germany.

Computational Biophysics and Biorobotics, Institute for Modelling and Simulation of Biomechanical Systems, Stuttgart Center for Simulation Science (SimTech), Universität Stuttgart, Nobelstraße 15, 70569, Stuttgart, Germany.

出版信息

Biomech Model Mechanobiol. 2020 Dec;19(6):2015-2047. doi: 10.1007/s10237-020-01322-7. Epub 2020 Apr 20.

DOI:10.1007/s10237-020-01322-7
PMID:32314072
Abstract

The load distribution among lumbar spinal structures-still an unanswered question-has been in the focus of this hybrid experimental and simulation study. First, the overall passive resistive torque-angle characteristics of healthy subjects' lumbar spines during flexion-extension cycles in the sagittal plane were determined experimentally by use of a custom-made trunk-bending machine. Second, a forward dynamic computer model of the human body that incorporates a detailed lumbar spine was used to (1) simulate the human-machine interaction in accordance with the experiments and (2) validate the modeled properties of the load-bearing structures. Third, the computer model was used to predict the load distribution in the experimental situation among the implemented lumbar spine structures: muscle-tendon units, ligaments, intervertebral discs, and facet joints. Nine female and 10 male volunteers were investigated. Lumbar kinematics were measured with a marker-based infrared device. The lumbar flexion resistance was measured by the trunk-bending machine through strain gauges on the axes of the machine's torque motors. Any lumbar muscle activity was excluded by simultaneous sEMG monitoring. A mathematical model was used to describe the nonlinear flexion characteristics. The subsequent extension branch of a flexion-extension torque-angle characteristic could be significantly distinguished from its flexion branch by the zero-torque lordosis angle shifted to lower values. A side finding was that the model values of ligament and passive muscle stiffnesses, extracted from well-established literature sources, had to be distinctly reduced in order to approach our measured overall lumbar stiffness values. Even after such parameter adjustment, the computer model still predicts too stiff lumbar spines in most cases in comparison with experimental data. A review of literature data reveals a deficient documentation of anatomical and mechanical parameters of spinal ligaments. For instance, rest lengths of ligaments-a very sensitive parameter for simulations-and cross-sectional areas turned out to be documented at best incompletely. Yet by now, our model well reproduces the literature data of measured pressure values within the lumbar disc at level L4/5. Stretch of the lumbar dorsal (passive) muscle and ligament structures as an inescapable response to flexion can fully explain the pressure values in the lumbar disc. Any further external forces like gravity, or any muscle activities, further increase the compressive load on a vertebral disc. The impact of daily or sportive movements on the loads of the spinal structures other than the disc cannot be predicted ad hoc, because, for example, the load distribution itself crucially determines the structures' current lever arms. In summary, compressive loads on the vertebral discs are not the major determinants, and very likely also not the key indicators, of the load scenario in the lumbar spine. All other structures should be considered at least equally relevant in the future. Likewise, load indicators other than disc compression are advisable to turn attention to. Further, lumbar flexion is a self-contained factor of lumbar load. It may be worthwhile, to take more consciously care of trunk flexion during daily activities, for instance, regarding long-term effects like lasting repetitive flexions or sedentary postures.

摘要

腰椎结构的负荷分布——这仍是一个悬而未决的问题——一直是这项混合实验和模拟研究的焦点。首先,通过使用定制的躯干弯曲机,实验确定了健康受试者在矢状面屈伸运动周期中腰椎的整体被动阻力-角度特性。其次,使用包含详细腰椎的正向动力学人体计算机模型,(1)根据实验模拟人机相互作用,(2)验证承载结构的建模特性。第三,使用计算机模型预测实验情况下实施的腰椎结构之间的负荷分布:肌肉-肌腱单位、韧带、椎间盘和小关节。研究了 9 名女性和 10 名男性志愿者。使用基于标记的红外设备测量腰椎运动学。通过机器扭矩电机轴上的应变计测量躯干弯曲机的腰椎弯曲阻力。通过同时进行 sEMG 监测排除任何腰椎肌肉活动。使用数学模型描述非线性弯曲特性。屈伸扭矩-角度特性的后续伸展分支可以通过移至较低值的零扭矩前凸角明显与弯曲分支区分开来。一个附带发现是,从既定文献来源提取的韧带和被动肌肉刚度的模型值必须明显降低,才能接近我们测量的整体腰椎刚度值。即使进行了这样的参数调整,计算机模型在大多数情况下仍然预测腰椎比实验数据更僵硬。对文献数据的回顾揭示了脊柱韧带解剖学和力学参数记录不足。例如,韧带的静止长度(模拟的一个非常敏感的参数)和横截面积最好记录不完整。然而,到目前为止,我们的模型很好地再现了在 L4/5 水平测量的腰椎间盘内的文献压力值数据。腰椎背侧(被动)肌肉和韧带结构的伸展是对弯曲的不可避免反应,可以完全解释腰椎间盘内的压力值。任何进一步的外部力,如重力或任何肌肉活动,都会进一步增加对椎间盘的压缩负荷。除了椎间盘之外,日常或运动活动对脊柱结构的负荷的影响不能专门预测,因为例如,负载分布本身对结构的当前力臂有决定性影响。总的来说,对椎间盘的压缩负荷不是腰椎负荷情况的主要决定因素,也不太可能是关键指标。未来应至少同等重视其他所有结构。同样,建议将注意力转向椎间盘压缩以外的其他负荷指标。此外,腰椎弯曲是腰椎负荷的一个独立因素。例如,在日常活动中更加有意识地注意躯干弯曲,对于长期影响(如持续重复弯曲或久坐姿势)可能是值得的。

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