Biomechanics and Movement Science, University of Delaware, Newark, DE 19716, United States.
J Electromyogr Kinesiol. 2012 Aug;22(4):607-11. doi: 10.1016/j.jelekin.2012.02.001. Epub 2012 Feb 29.
Antagonistic muscle activity can impair performance, increase metabolic cost, and increase joint stability. Excessive antagonist muscle activity may also cause an undesirable increase in joint contact forces in certain populations such as persons with knee osteoarthritis. Co-contraction of antagonistic muscles measured by electromyography (EMG) is a popular method used to infer muscle forces and subsequent joint forces. However, EMG alone cannot completely describe joint loads that are experienced. This study compares a co-contraction index from EMG to a co-contraction index calculated from simulated muscle moments during gait. Co-contraction indices were calculated from nine healthy, able-bodied subjects during treadmill walking at self-selected speed. Musculoskeletal simulations that tracked experimental kinematics and kinetics were generated for each subject. Experimentally measured EMG was used to constrain the model's muscle excitation for the vastus lateralis and semimembranosus muscles. Using the model's excitations as constrained by EMG, muscle activation and muscle moments were calculated. A common co-contraction index (CCI) based on EMG was compared with co-contraction based on normalized modeled muscle moments (MCCI). While the overall patterns were similar, the co-contraction predicted by MCCI was significantly lower than CCI. Because a simulation can account for passive muscle forces not detected with traditional EMG analysis, MCCI may better reflect physiological knee joint loads. Overall, the application of two co-contraction methods provides a more complete description of muscle co-contraction and joint loading than either method individually.
拮抗肌活动会降低运动表现、增加代谢成本并降低关节稳定性。在某些人群（如膝骨关节炎患者）中，过度的拮抗肌活动可能会导致关节接触力的不期望增加。肌电图（EMG）测量的拮抗肌协同收缩是一种常用的推断肌肉力量和随后关节力的方法。然而，EMG 本身并不能完全描述所经历的关节负荷。本研究比较了 EMG 得出的协同收缩指数与步态模拟肌肉力矩得出的协同收缩指数。在自我选择的速度下，对 9 名健康、健全的受试者在跑步机上行走时的协同收缩指数进行了计算。为每个受试者生成了跟踪实验运动学和动力学的肌肉骨骼模拟。使用实验测量的 EMG 来约束模型对股外侧肌和半膜肌的肌肉激发。根据 EMG 约束模型的激发，计算了肌肉激活和肌肉力矩。将基于 EMG 的常见协同收缩指数（CCI）与基于归一化模拟肌肉力矩的协同收缩指数（MCCI）进行了比较。尽管总体模式相似，但 MCCI 预测的协同收缩明显低于 CCI。由于模拟可以考虑到传统 EMG 分析无法检测到的被动肌肉力，因此 MCCI 可能更好地反映了生理膝关节负荷。总体而言，两种协同收缩方法的应用比单独使用任何一种方法都能更全面地描述肌肉协同收缩和关节加载情况。
