评估不同耐力训练负载的奥林匹克运动员对自行车运动的心脏自主反应:基于多层次探索性因子分析的统计指标的新见解
Nadia Solaro1, Massimo Pagani2, Antonio Spataro3
1Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy.
Frontiers in physiology
|November 2, 2023
概括
这项研究引入了一种使用多层探索性因子分析 (MEFA) 的新方法,以简化运动员的心率变化 (HRV) 分析. MEFA将复杂的HRV数据减少到更少的指标中,提供了对运动期间自主神经系统 (ANS) 反应的更清晰的见解.
科学领域:
- 运动生理学 运动生理学
- 自主神经系统研究 自主神经系统研究
- 运动科学 运动科学 运动科学
背景情况:
- 了解自主神经系统 (ANS) 对运动的反应是复杂的.
- 心率变化 (HRV) 分析为研究ANS提供了一种方便的方法.
- 在不同时间段解释众多相关的人力资源价值指数存在挑战.
研究的目的:
- 提出一种新的方法,多层次探索性因子分析 (MEFA),用于分析精英运动员对运动的心脏自主反应.
- 将 HRV 衍生指数的多样性减少到更少的无关联的 ANS 指标.
- 为了克服在练习期间解释复杂HRV数据的困难.
主要方法:
- 涉及30名意大利奥运运动员 (15名骑自行车运动员,15名射击运动员).
- 使用了一个动态的协议,包括休息,逐步炼 (有氧到无氧) 和恢复.
- 通过光谱分析计算了12个ANS代理,跨越9个时间段,使用MEFA进行分析.
主要成果:
- 导出了两个全球ANS指标 (振幅,频率) 和三个动态ANS指标 (振幅,自相似性,振荡).
- 骑自行车的人表现出明显更高的全局幅度和更低的频率比射手,这表明了副交感的主导地位.
- 动态指标有效地检测出休息,运动和恢复之间的变化,区分运动员群体.
结论:
- MEFA提供了一种简化表达在炼期间的ANS调制.
- 这种方法有助于解释HRV衍生指数.
- 应用MEFA增强了非侵入性HRV分析在体育中的实际应用潜力.
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