Granata K P, Marras W S
Biodynamics Laboratory, Ohio State University, Columbus 43210.
J Biomech. 1993 Dec;26(12):1429-38. doi: 10.1016/0021-9290(93)90093-t.
An EMG-assisted, low-back, lifting model is presented which simulates spinal loading as a function of dynamic, asymmetric, lifting exertions. The purpose of this study has been to develop a model which overcomes the limitations of previous models including static or isokinetic mechanics, inaccurate predictions of muscle coactivity, static interpretation of myoelectric activity, and physiologically unrealistic or variable muscle force per unit area. The present model predicts individual muscle forces from processed EMG data, normalized as a function of trunk angle and asymmetry, and modified to account for muscle length and velocity artifacts. The normalized EMGs are combined with muscle cross-sectional area and intrinsic strength capacity as determined on a per subject basis, to represent tensile force amplitudes. Dynamic internal and external force vectors are employed to predict trunk moments, spinal compression, lateral and anterior shear forces. Data from 20 subjects performing a total of 2160 exertions showed good agreement between predicted and measured values under all trunk angle, asymmetry, velocity, and acceleration conditions. The design represents a significant step toward accurate, fully dynamic modeling of the low-back in multiple dimensions. The benefits of such a model are the insights provided into the effects of motion induced, muscle co-activity on spinal loading in multiple dimensions.
本文提出了一种肌电图辅助的下背部举重模型，该模型可模拟脊柱负荷与动态、不对称举重用力的函数关系。本研究的目的是开发一种模型，克服以往模型的局限性，包括静态或等速力学、肌肉共同激活预测不准确、肌电活动的静态解释以及生理上不现实或单位面积可变的肌肉力量。当前模型根据处理后的肌电图数据预测个体肌肉力量，将其归一化为躯干角度和不对称性的函数，并进行修正以考虑肌肉长度和速度伪影。归一化的肌电图与根据个体确定的肌肉横截面积和固有力量能力相结合，以表示拉伸力幅度。采用动态内外力矢量来预测躯干力矩、脊柱压缩、侧向和前向剪切力。来自20名受试者共进行2160次用力的数据表明，在所有躯干角度、不对称性、速度和加速度条件下，预测值与测量值之间具有良好的一致性。该设计朝着在多个维度上对下背部进行准确、全动态建模迈出了重要一步。这种模型的好处是能够深入了解运动引起的肌肉共同激活在多个维度上对脊柱负荷的影响。
