雷达传感器数据适用于准确的线性冲刺建模
Daniel Geneau1,2, Patrick Cormier1,2, Ming-Chang Tsai1
1Canadian Sport Institute Pacific, Victoria, BC V9E 2C5, Canada.
Sensors (Basel, Switzerland)
|December 17, 2024
概括
雷达传感器通过准确捕获速度数据来改善冲刺性能分析. 使用先进的建模技术,如sigmoid和多项式函数,可以提高运动员的力-速度概况的可靠性.
科学领域:
- 体育科学 运动科学 运动科学
- 生物力学 生物力学
- 竞技表现分析 竞技表现分析
背景情况:
- 准确的线性冲刺建模对于评估运动员的力量,功率和速度能力至关重要.
- 雷达传感器提供精确的速度数据,对于可靠的力-速度 (FV) 配置文件至关重要.
- 这项研究研究了将雷达传感器数据与各种冲刺建模技术相匹配,以提高FV配置的准确性.
研究的目的:
- 用雷达收集的速度数据来评估不同冲刺建模技术的适用性.
- 为了比较各种建模方法对衍生力-速度指标的影响.
- 确定最佳的建模策略,以增强冲刺绩效分析.
主要方法:
- 47名大学运动员进行了两次40米冲刺,雷达传感器记录了速度数据.
- 评估了五种建模方法:三种已确定的方法,一个三度多项式和一个西格函数.
- 使用根平均平方误差 (RMSE) 和确定系数 (r2) 评估适用性;使用ANOVA比较FV指标.
主要成果:
- 在测试模型中,在适合性和大多数FV指标中发现了显著的差异 (p < 0.001).
- 与其他方法相比,西格形和多项式函数与雷达收集的速度数据相匹配更好.
- 这些发现突出了建模技术对衍生的冲刺绩效指标准确性的影响.
结论:
- 雷达传感器与适当的建模技术相结合,可显著提高冲刺性能分析的准确性.
- 立方体和多项式函数为使用雷达速度数据进行FV分析提供了更高的准确性.
- 培训师和研究人员应注意选择的建模方法,以确保在研究中得到一致和可比的结果.
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