Department of Mechanical Engineering, University of Melbourne, Victoria, AUSTRALIA.
Med Sci Sports Exerc. 2022 Nov 1;54(11):1961-1972. doi: 10.1249/MSS.0000000000002978. Epub 2022 Jun 23.
We combined a full-body musculoskeletal model with dynamic optimization theory to predict the biomechanics of maximum-speed sprinting and evaluate the effects of changes in muscle-tendon properties on sprint performance.
The body was modeled as a three-dimensional skeleton actuated by 86 muscle-tendon units. A simulation of jogging was used as an initial guess to generate a predictive dynamic optimization solution for maximum-speed sprinting. Nominal values of lower-limb muscle strength, muscle fascicle length, muscle intrinsic maximum shortening velocity (fiber-type composition), and tendon compliance were then altered incrementally to study the relative influence of each property on sprint performance.
Model-predicted patterns of full-body motion, ground forces, and muscle activations were in general agreement with experimental data recorded for maximum-effort sprinting. Maximum sprinting speed was 1.3 times more sensitive to a change in muscle strength compared with the same change in muscle fascicle length, 2.0 times more sensitive to a change in muscle fascicle length compared with the same change in muscle intrinsic maximum shortening velocity, and 9.1 times more sensitive to a change in muscle intrinsic maximum shortening velocity compared with the same change in tendon compliance. A 10% increase in muscle strength increased maximum sprinting speed by 5.9%, whereas increasing muscle fascicle length, muscle intrinsic maximum shortening velocity, and tendon compliance by 10% increased maximum sprinting speed by 4.7%, 2.4%, and 0.3%, respectively.
Sprint performance was most sensitive to changes in muscle strength and least affected by changes in tendon compliance. Sprint performance was also more heavily influenced by changes in muscle fascicle length than muscle intrinsic maximum shortening velocity. These results could inform training methods aimed at optimizing performance in elite sprinters.
我们结合了全身肌肉骨骼模型和动态优化理论，以预测最大速度冲刺的生物力学，并评估肌肉-肌腱特性变化对冲刺性能的影响。
身体被建模为一个由 86 个肌肉-肌腱单元驱动的三维骨骼。慢跑模拟被用作初始猜测，以生成最大速度冲刺的预测动态优化解决方案。然后，逐步改变下肢肌肉力量、肌肉束长度、肌肉内在最大缩短速度（纤维类型组成）和肌腱顺应性的名义值，以研究每种特性对冲刺性能的相对影响。
模型预测的全身运动、地面力和肌肉激活模式与最大努力冲刺中记录的实验数据基本一致。最大冲刺速度对肌肉力量变化的敏感度是肌肉束长度变化的 1.3 倍，对肌肉束长度变化的敏感度是肌肉内在最大缩短速度变化的 2.0 倍，对肌肉内在最大缩短速度变化的敏感度是肌腱顺应性变化的 9.1 倍。肌肉力量增加 10%可使最大冲刺速度提高 5.9%，而肌肉束长度、肌肉内在最大缩短速度和肌腱顺应性分别增加 10%，可使最大冲刺速度提高 4.7%、2.4%和 0.3%。
冲刺性能对肌肉力量变化最敏感，对肌腱顺应性变化最不敏感。冲刺性能受肌肉束长度变化的影响也大于肌肉内在最大缩短速度变化的影响。这些结果可以为旨在优化精英短跑运动员表现的训练方法提供信息。
