强力-速度-功率分析与传统的力量测量方法对比,用于预测运动员表现
Tobias Buk Jørgensen1, Nicklas Junge2, Jesper Lundbye-Jensen2
1Section of Movement and Neuroscience, Department of Nutrition, Exercise and Sports, University of Copenhagen, Copenhagen, Denmark - tbjorgensen@nexs.ku.dk.
The Journal of sports medicine and physical fitness
|July 7, 2025
概括
力量-速度-功率分析,特别是最大功率 (Pmax),显示出与运动表现的强烈关联,超过了评估神经肌肉能力的传统同位体峰值力 (IPF) 和一次重复最大 (1RM) 测试.
科学领域:
- 运动科学 运动科学 运动科学
- 生物力学 生物力学
- 运动生理学 运动生理学
背景情况:
- 传统的力量测试,如同位数峰值力 (IPF) 和一次重复最大 (1RM),可能无法完全捕捉与运动表现相关的神经肌肉参数.
- 力量-速度-功率 (FVP) 分析提供了对神经肌肉功能的更具动态性的评估.
研究的目的:
- 为了比较FVP分析 (最大功率-Pmax) 与同位体峰值力 (IPF) 和一次重复最大 (1RM) 与运动绩效指标的关联.
- 确定FVP变量的附加值,包括力-速度不平衡 (FVimb),用于预测性能.
主要方法:
- 一项涉及84名体育科学学生 (35名女性,49名男性) 的横截面研究.
- 测量了半个坐的IPF,1RM和坐跳跃的FVP衍生的Pmax.
- 评估垂直跳跃,线性冲刺和改变方向 (COD) 的表现.
- 使用了皮尔森的相关性和多重线性回归分析.
主要成果:
- IPF仅显示了与冲刺表现的小相关性.
- 1RM与所有绩效指标都显示出中等至大相关性.
- Pmax与所有性能指标均呈现中度至非常大,高度显著的相关性.
- 包括FVimb在内显著提高了Pmax对冲刺和COD性能的预测能力.
结论:
- 与IPF和1RM相比,FVP分析,特别是Pmax,对爆炸性的运动表现提供了更深入的见解.
- 在评估运动员神经肌肉功能能力方面,FVP措施提供了附加值.
- 这些发现支持将FVP分析纳入运动员评估协议.
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