Kaufman K R, An K W, Litchy W J, Chao E Y
Motion Analysis Laboratory, Children's Hospital, San Diego, CA 92123.
Neuroscience. 1991;40(3):781-92. doi: 10.1016/0306-4522(91)90012-d.
A physiological model for predicting muscle forces is described. Rigid-body mechanics and musculoskeletal physiology are used to describe the dynamics of the segment model and muscle model. Unknown muscle and joint contact forces outnumber the equilibrium equations resulting in an indeterminate problem. Mathematical optimization is utilized to resolve the indeterminacy. The modeling procedure relies entirely on established physiological principles. Data describing the muscle anatomy and body structures are included. A model defining the force-length-velocity-activation relationship of a muscle is adopted. The force a muscle produces is assumed to be proportional to its maximum stress, physiological cross-sectional area, activation, and its functional configurations including the muscle architecture, muscle length, contracting velocity, and passive tension. These factors are incorporated into inequality equations which limit the force for each muscle. Minimal muscular activation is forwarded as the optimization criterion for muscle force determination.
描述了一种用于预测肌肉力量的生理模型。刚体力学和肌肉骨骼生理学被用于描述节段模型和肌肉模型的动力学。未知的肌肉和关节接触力的数量超过了平衡方程,导致问题具有不确定性。利用数学优化来解决这种不确定性。建模过程完全依赖于已确立的生理原理。其中包括描述肌肉解剖结构和身体结构的数据。采用了一个定义肌肉力-长度-速度-激活关系的模型。假定肌肉产生的力与其最大应力、生理横截面积、激活以及其功能配置(包括肌肉结构、肌肉长度、收缩速度和被动张力)成正比。这些因素被纳入不等式方程,以限制每块肌肉的力。将最小肌肉激活作为确定肌肉力量的优化标准。