The purpose of this study was to use wearable technology data to quantify alterations in subject-specific running patterns throughout a marathon race and to determine if runners could be clustered into subgroups based on similar trends in running gait alterations throughout the marathon. Using a wearable sensor, data were collected for cadence, braking, bounce, pelvic rotation, pelvic drop, and ground contact time for 27 runners. A composite index was calculated based on the "typical" data (4-14 km) for each runner and evaluated for 14 individual 2-km sections thereafter to detect "atypical" data (ie, higher indices). A cluster analysis assigned all runners to a subgroup based on similar trends in running alterations. Results indicated that the indices became significantly higher starting at 20 to 22 km. Cluster 1 exhibited lower indices than cluster 2 throughout the marathon, and the only significant difference in characteristics between clusters was that cluster 1 had a lower age-grade performance score than cluster 2. In summary, this study presented a novel method to investigate the effects of fatigue on running biomechanics using wearable technology in a real-world setting. Recreational runners with higher age-grade performance scores had less atypical running patterns throughout the marathon compared with runners with lower age-grade performance scores.

中文翻译：

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可穿戴技术数据的新考虑：马拉松期间跑步生物力学的变化。

本研究的目的是使用可穿戴技术数据来量化马拉松比赛中特定主题的跑步模式的变化，并确定是否可以根据马拉松比赛中跑步步态变化的相似趋势将跑步者分成亚组。使用可穿戴传感器，收集了 27 名跑步者的踏频、制动、弹跳、骨盆旋转、骨盆下垂和接地时间的数据。根据每个跑步者的“典型”数据（4-14 公里）计算综合指数，然后对 14 个单独的 2 公里路段进行评估，以检测“非典型”数据（即更高的指数）。聚类分析根据跑步变化的相似趋势将所有跑步者分配到一个子组。结果表明，从 20 到 22 公里开始，这些指数显着升高。在整个马拉松比赛中，集群 1 的指数低于集群 2，集群之间唯一显着的特征差异是集群 1 的年龄等级表现得分低于集群 2。 总之，本研究提出了一种研究效果的新方法在现实世界环境中使用可穿戴技术运行生物力学的疲劳。与年龄等级成绩得分较低的跑步者相比，年龄等级成绩得分较高的休闲跑步者在整个马拉松比赛中的非典型跑步模式较少。这项研究提出了一种新方法，可以在现实环境中使用可穿戴技术来研究疲劳对跑步生物力学的影响。与年龄等级成绩得分较低的跑步者相比，年龄等级成绩得分较高的休闲跑步者在整个马拉松比赛中的非典型跑步模式较少。这项研究提出了一种新方法，可以在现实环境中使用可穿戴技术来研究疲劳对跑步生物力学的影响。与年龄等级成绩得分较低的跑步者相比，年龄等级成绩得分较高的休闲跑步者在整个马拉松比赛中的非典型跑步模式较少。