Arjmand N, Plamondon A, Shirazi-Adl A, Parnianpour M, Larivière C
Institut de recherche Robert Sauvé en santé et en sécurité du travail, Montréal, Québec, Canada.
Clin Biomech (Bristol). 2012 Jul;27(6):537-44. doi: 10.1016/j.clinbiomech.2011.12.015. Epub 2012 Jan 20.
Asymmetric lifting activities are associated with low back pain.
A finite element biomechanical model is used to estimate spinal loads during one- and two-handed asymmetric static lifting activities. Model input variables are thorax flexion angle, load magnitude as well as load sagittal and lateral positions while response variables are L4-L5 and L5-S1 disc compression and shear forces. A number of levels are considered for each input variable and all their possible combinations are introduced into the model. Robust yet user-friendly predictive equations that relate model responses to its inputs are established.
Predictive equations with adequate goodness-of-fit (R(2) ranged from ~94% to 99%, P≤0.001) that relate spinal loads to task (input) variables are established. Contour plots are used to identify combinations of task variable levels that yield spine loads beyond the recommended limits. The effect of uncertainties in the measurements of asymmetry-related inputs on spinal loads is studied.
A number of issues regarding the NIOSH asymmetry multiplier are discussed and it is concluded that this multiplier should depend on the trunk posture and be defined in terms of the load vertical and horizontal positions. Due to an imprecise adjustment of the handled load magnitude this multiplier inadequately controls the biomechanical loading of the spine. Ergonomists and bioengineers, faced with the dilemma of using either complex but more accurate models on one hand or less accurate but simple models on the other hand, have hereby easy-to-use predictive equations that quantify spinal loads under various occupational tasks.
不对称的提举活动与腰痛有关。
使用有限元生物力学模型来估计单手和双手不对称静态提举活动期间的脊柱负荷。模型输入变量为胸廓屈曲角度、负荷大小以及负荷的矢状位和侧方位置，而响应变量为L4-L5和L5-S1椎间盘的压缩力和剪切力。每个输入变量考虑多个水平，并将其所有可能的组合引入模型。建立了将模型响应与其输入相关联的稳健且用户友好的预测方程。
建立了将脊柱负荷与任务（输入）变量相关联的具有足够拟合优度的预测方程（R²范围从约94%到99%，P≤0.001）。等高线图用于识别产生超出推荐极限的脊柱负荷的任务变量水平组合。研究了与不对称相关的输入测量中的不确定性对脊柱负荷的影响。
讨论了关于美国国家职业安全与健康研究所（NIOSH）不对称乘数的一些问题，并得出结论，该乘数应取决于躯干姿势，并根据负荷的垂直和水平位置来定义。由于对搬运负荷大小的调整不精确，该乘数无法充分控制脊柱的生物力学负荷。面对一方面使用复杂但更准确的模型，另一方面使用不太准确但简单的模型这一两难困境的人类工效学家和生物工程师，现在有了易于使用的预测方程，可量化各种职业任务下的脊柱负荷。
