A hierarchical cluster analysis to determine whether injured runners exhibit similar kinematic gait patterns
A hierarchical cluster analysis to determine whether injured runners exhibit similar kinematic gait patterns
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DOI：
10.1111/sms.13624
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发表时间：
2020-01-22
影响因子：
4.1
通讯作者：
Ferber, Reed
中科院分区：
文献类型：
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作者：
Jauhiainen, Susanne;Pohl, Andrew J.;Ferber, Reed
以前的研究表明，跑步者可以根据相同的步态模式进行分组；然而，之前没有研究评估过这样的亚组在各种损伤的个体中的存在。因此，本研究的目的是评估是否可以在一大群受伤和健康的跑步者中识别出具有相同跑步模式的不同亚组，以及所识别的亚组是否与特定的损伤位置相关。对291名受伤和健康的跑步者的三维运动学数据进行了等级聚类分析，这些数据代表了不同性别和不同年龄(10-66岁)。聚类分析从数据中发现了五个不同的亚组。用单因素方差分析(ANOVA)比较亚组之间的运动学差异。与我们的假设相反，具有相同损伤类型的跑步者并没有聚集在一起，但不同损伤在亚组中的分布在整个样本中是相似的。这些结果表明，相同的步态模式独立于损伤位置而存在，在计划损伤预防或康复策略时，考虑这些潜在的模式是重要的。
Previous studies have suggested that runners can be subgrouped based on homogeneous gait patterns; however, no previous study has assessed the presence of such subgroups in a population of individuals across a wide variety of injuries. Therefore, the purpose of this study was to assess whether distinct subgroups with homogeneous running patterns can be identified among a large group of injured and healthy runners and whether identified subgroups are associated with specific injury location. Three-dimensional kinematic data from 291 injured and healthy runners, representing both sexes and a wide range of ages (10-66 years), were clustered using hierarchical cluster analysis. Cluster analysis revealed five distinct subgroups from the data. Kinematic differences between the subgroups were compared using one-way analysis of variance (ANOVA). Against our hypothesis, runners with the same injury types did not cluster together, but the distribution of different injuries within subgroups was similar across the entire sample. These results suggest that homogeneous gait patterns exist independent of injury location and that it is important to consider these underlying patterns when planning injury prevention or rehabilitation strategies.