模型心率动态与速度和功率输出在冲刺皮划艇作为训练评估和优化培训的基础
Gielen Jasper1, Catherine Smets1, Noor Vidts1
1M3-BIORES, Department of Biosystems, KU Leuven, Leuven, Belgium.
European journal of sport science
|December 13, 2024
概括
这项研究使用先进的数据分析对精英独木舟短跑运动员的外部训练强度和心率 (HR) 进行了建模. 时间变化的模型准确地将功率输出和速度与HR联系起来,增强训练优化.
科学领域:
- 运动科学 运动科学 运动科学
- 生物机械工程 生物机械工程
- 运动生理学 运动生理学
背景情况:
- 功率输出传感器和运动数据分析的进步使训练强度的详细研究成为可能.
- 了解外部负荷和内部生理反应之间的关系对于优化运动表现至关重要.
- 平水艇冲刺对准确测量和建模训练强度提出了独特的挑战.
研究的目的:
- 开发和验证模型,将外部训练强度 (速度,功率输出) 与心率 (HR) 的时间序列联系起来.
- 确定最佳的自回归-外源 (ARX) 建模配置,以分析外部负载和内部HR响应之间的动态关系.
- 探索这些模型的实用性,以改善划船运动中的训练评估和优化.
主要方法:
- 9名精英运动员完成了47次不同强度的间歇训练.
- 持续收集HR,速度和功率的数据,并通过感知劳动和血液乳酸盐测量来补充.
- 测试各种自回归-外源 (ARX) 模型配置,包括输入变量 (速度与功率),模型顺序 (第一与第二),以及参数估计 (时间不变与时间变化).
主要成果:
- 自主回归-外源 (ARX) 模型表现出强的性能,平均R平方值在0.60到0.97.9之间.
- 具有时间变化的参数估计的第一阶模型实现了最佳性能,平均R平方值为0.94.
- 时间变化的建模参数与个体运动员水平的运动强度指标有显著的相关性.
结论:
- 动态建模提供了一种强大的方法,可以将外部训练负载与冲刺划艇中的心率反应联系起来.
- 在ARX模型中,时间变化的参数估计对于捕捉外部和内部培训措施之间的复杂关系是优越的.
- 这些经过验证的模型提供了一种有价值的工具,可以增强精英划艇短跑者的培训计划的评估和优化.
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