在基于证据的分类中对多种损伤措施进行集群分析,用于准高山滑雪滑雪者
Kaiqi Liu1, Linhong Ji1, Han Ma1
1State Key Laboratory of Tribology, Department of Mechanical Engineering, Tsinghua University, Beijing, China.
Scandinavian journal of medicine & science in sports
|October 13, 2023
概括
通过使用损伤和性能测试,改善了准高山坐滑滑的分类. 对干部强度,运动范围 (ROM) 和肌肉激发的集群分析创造了有效的运动员群体,提高了分类准确性.
科学领域:
- 运动科学 运动科学 运动科学
- 生物力学 生物力学
- 在残奥会分类中,残奥会分类.
背景情况:
- 国际残奥会委员会主张基于证据的分类,以尽量减少主观性.
- 帕拉阿尔卑斯式坐着滑雪的分类需要有效的损伤和性能指标.
- 当前的分类系统可以从客观,数据驱动的方法中受益.
研究的目的:
- 为了评估减弱和性能测试对帕拉高山坐滑滑雪分类的有效性.
- 确定这些措施的集群分析是否可以创建一个有效的分类结构.
- 通过结合运动范围 (ROM) 和肌肉刺激来提高分类准确性.
主要方法:
- 三十八名帕拉阿尔卑斯式坐姿滑雪者接受了七项测试,测量了对称的树干强度,肌肉刺激,ROM和模拟的滑雪表现 (板倾斜角度).
- 计算了减弱度和板的倾斜角度之间的相关性.
- 在K-means集群分析中,根据损伤指标对表现的影响,将运动员分组为组.
主要成果:
- 在所有测量和最大板倾斜角度之间发现了显著的相关性 (r = 0.35-0.81,p < 0.05).
- 集群分析,将ROM和肌肉激发与强度相结合,提高了分类准确度 (53%-79%).
- 确定了四个具有强大的结构 (平均轮系数 = 0.81) 和显著的集群间差异的独特集群.
结论:
- 评估的测试和集群分析为帕拉阿尔卑斯山坐滑滑雪的分类提供了有效的框架.
- 将ROM和肌肉刺激与强度测量相结合,可以显著提高分类准确性.
- 这种以证据为基础的方法可以带来更透明的分类系统,并作为其他残疾人运动的典范.
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