Hughes R E, An K N
Biomechanics Laboratory, Mayo Clinic, Rochester, MN 55905, USA.
Med Biol Eng Comput. 1997 Sep;35(5):544-8. doi: 10.1007/BF02525538.
Although variability of anthropometric measures within a population is a well established phenomenon, most biomechanical models are based on average parameter values. For example, optimisation models for predicting muscle forces from net joint reaction moments typically use average muscle moment arms. However, understanding the distribution of musculoskeletal morbidity within a population requires information about the variation of tissue loads within the population. This study investigated the use of Monte Carlo simulation techniques to predict the statistical distribution of deltoid and rotator cuff muscle forces during static arm elevation. Muscle moment arms were modelled either as independent random variables or jointly distributed random variables. Moment arm data was collected on 22 cadaver specimens. The results demonstrated the use of Monte Carlo techniques to describe the statistical distribution of muscle forces. Although assuming statistically independent moment arms did affect the statistical distribution shape, that assumption did not affect the median predicted forces. The standard deviations of muscle forces predicted using Monte Carlo techniques were similar to the standard deviation of muscle force predictions using the whole sample of specimens. It is concluded that Monte Carlo simulation techniques are a useful tool to analyse the interindividual variability of rotator cuff muscle forces.
尽管人群中人体测量指标的变异性是一个已被充分证实的现象，但大多数生物力学模型都是基于平均参数值构建的。例如，用于从净关节反应力矩预测肌肉力量的优化模型通常使用平均肌肉力臂。然而，了解人群中肌肉骨骼疾病的分布需要有关人群中组织负荷变化的信息。本研究调查了使用蒙特卡罗模拟技术来预测静态手臂抬高过程中三角肌和肩袖肌群力量的统计分布。肌肉力臂被建模为独立随机变量或联合分布随机变量。在22个尸体标本上收集了力臂数据。结果表明了使用蒙特卡罗技术来描述肌肉力量的统计分布。尽管假设统计上独立的力臂确实会影响统计分布形状，但该假设并不影响预测力的中位数。使用蒙特卡罗技术预测的肌肉力量标准差与使用整个标本样本预测的肌肉力量标准差相似。得出的结论是，蒙特卡罗模拟技术是分析肩袖肌群力量个体间变异性的有用工具。
