复杂的网络应用于运动员和适度活跃的两性受试者在30秒的全面测试中
Guilherme F Rizatto1,2, Fúlvia B Manchado-Gobatto3, Ivan G Dos Reis4
1Laboratory of Applied Sport Physiology - LAFAE, School of Applied Sciences, University of Campinas, UNICAMP, Limeira, Brazil - guifrizatto@gmail.com.
The Journal of sports medicine and physical fitness
|June 4, 2025
概括
复杂的网络分析显示,性别和健身水平在非机动跑步机 (NMT) 上的30秒全力以赴跑步测试 (AO30) 中显著影响关键性能指标. 这些发现强调了在体育表现分析中考虑个体差异的重要性.
科学领域:
- 运动科学和生物力学
- 运动生理学 运动生理学
- 复杂网络分析 (CNA)
背景情况:
- 复杂网络分析 (CNA) 是识别运动表现中的关键参数的宝贵工具.
- 在非机动跑步机 (NMT) 上进行30秒全力以赴的跑步测试 (AO30) 是体育中CNA的常见协议.
- 个别因素,如健身水平和性别,可以改变不同参数对AO30结果的影响.
研究的目的:
- 调查调节水平和性别如何影响AO30测试中最有影响力的性能参数.
- 应用复杂的网络分析来区分各种参与者群体的关键绩效指标.
主要方法:
- 分析了72名参与者 (36名男性,36名女性) 的数据,分类为中度活跃或篮球运动员.
- 收集的机械 (力,功率,速度,疲劳指数),人体 (体重,身高,BMI) 和生理 (血液乳酸) 数据.
- 在CNA中利用中心性指标 (程度,中间性,自向量,PageRank) 针对四个不同的群体:中度活跃的男性 (M
MA ),男性篮球运动员 (MPA ),中度活跃的女性 (WMA ) 和女性篮球运动员 (WPA ).
主要成果:
- 平均功率对中度活动的男性 (M
MA ) 和女篮运动员 (WPA ) 有很大的影响. - 对于中度活跃的女性 (W
MA ),血中的乳酸相对于体重是最重要的变量. - 男篮运动员 (M
PA ) 显示身体质量,最大功率和平均力是最有影响力的参数.
结论:
- 该研究证实,个体的性别和条件水平都对通过CNA在NMT的AO30测试中识别的关键性能参数有显著的影响.
- 这些发现强调了在体育表现评估中需要量身定制的分析方法,考虑到人口统计和健康状况的变化.
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