在羽毛球前手空中撞击期间进行肌肉协同分析:整合肌电图和肌肉骨建模
Raheleh Tajik1, Wissem Dhahbi2,3, Hamed Fadaei1
1Department of Biomechanics and Sports Injuries, Faculty of Physical Education and Sports Sciences, Kharazmi University, Tehran, Iran.
Frontiers in sports and active living
|June 18, 2025
概括
这项研究验证了肌肉骨模型,用于分析羽毛球击败期间的肩膀肌肉协同作用,使用非负矩阵因子化 (NMF). 结果显示实验和模拟数据之间的高度一致,支持MSK模型用于体育科学应用.
科学领域:
- 生物力学 生物力学
- 运动科学 运动科学 运动科学
- 发动机控制器的控制器
背景情况:
- 了解肩膀肌肉协调对于优化表现和预防羽毛球等高空运动中的伤害至关重要.
- 高速运动对准确测量神经肌肉活动提出了挑战.
研究的目的:
- 用非负矩阵分解 (NMF) 来量化羽毛球前手空中冲击 (BFOS) 期间的肩膀肌肉协同作用.
- 通过将NMF衍生电肌图 (EMG) 协同效应与模拟结果进行比较,对高速运动的肌肉骨 (MSK) 模型进行验证.
- 探索基于NMF的MSK模型在促进体育科学研究中的实用性.
主要方法:
- 20名顶级羽毛球运动员进行了最大努力的BFOS,同时记录了15个肩肌的EMG信号.
- 三维运动分析捕获了动力学数据,一个经过验证的OpenSim上肢模型模拟了肌肉激活.
- NMF从实验EMG和MSK建模数据中提取了协同作用向量和激活系数.
主要成果:
- 三种肌肉协同作用解释了实验和模拟数据中90%以上的差异.
- 在EMG衍生的和MSK模型衍生的协同效应之间发现了强烈的一致性 (权重向量:0.81-0.88,激活系数:0.95-0.98).
- 在下形激活中发现了微小的差异,可能是由于表面EMG的限制.
结论:
- 强烈的对应性验证了MSK模型用于分析高速空中运动中的神经肌肉控制的使用.
- 确定了肌肉协同作用,为了解BFOS协调提供了一个框架.
- 这些发现支持优化训练计划和开发空中运动员伤害预防策略的应用.
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