Clustering classification of cyclists according to the acute fatigue outcomes produced by an ultra-endurance event

IF 0.5 Q4 SPORT SCIENCES
J. Sanchez-Jimenez
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Abstract

This study aimed to analyze the differences between clusters obtained by the acute effect of fatigue after an ultra-endurance event in the internal and external load of cyclists. 26 volunteers participated in the study, and they were divided into the experimental group (N = 18; height: 177 ± 8 cm; body mass: 78.6 ± 10.3 kg) and the control group (N = 8; height: 176 ± 10 cm; body mass: 78.0 ± 15.7 kg). The experimental group completed a 12 h non-stop cycling event. Jump height, lactate, plasma antioxidant capacity, pain perception and fatigue perception were measured before and after the event. Cyclists of the experimental group were classified considering their training characteristics (recreational vs. competitive) and by conducting a non-supervised K-means clustering. The differentiation of cyclists according to training characteristics resulted in a lower distance covered by recreational than competitive cyclists (279.4 ± 39.7 km vs. 371.0 ± 71.7 km; ES ≥ 0.8; p < 0.01), although no differences were observed in the remaining variables between groups (p > 0.05). The clustering analysis provided two clusters. Cluster 2 suffered a greater jump height reduction (-3.3 ± 1.6 vs. 1.2 ± 0.8; ES ≥ 0.8; p < 0.001) and increased pain and fatigue perception (ES ≥ 0.5; p < 0.05) after the race than Cluster 1. In conclusion, counter-movement jump can differentiate the fatigue produced by a cycling ultra-endurance event and therefore, this non-invasive technique is useful in fatigue monitoring and recovery planification.
根据超耐力赛事产生的急性疲劳结果对骑自行车者进行聚类分类
本研究旨在分析超长耐力赛事后疲劳急性效应对骑行者内外负荷的影响。26名志愿者参与了这项研究,他们被分为实验组(N = 18;高度:177±8cm;体重:78.6±10.3 kg)和对照组(N = 8;高度:176±10厘米;体重:78.0±15.7 kg)。实验组完成12小时不间断自行车比赛。测定运动前后的跳高、乳酸、血浆抗氧化能力、疼痛感和疲劳感。实验组的骑自行车者根据他们的训练特征(娱乐性与竞技性)进行分类,并通过进行无监督k均值聚类。骑自行车者训练特征的差异导致休闲骑行距离低于竞技骑行距离(279.4±39.7 km vs 371.0±71.7 km);Es≥0.8;P < 0.01),其余变量组间差异无统计学意义(P > 0.05)。聚类分析提供了两个聚类。第二组的跳跃高度降低幅度更大(-3.3±1.6 vs. 1.2±0.8);Es≥0.8;p < 0.001),疼痛和疲劳知觉增加(ES≥0.5;p < 0.05)。总之,反向运动跳跃可以区分自行车超耐力赛事产生的疲劳,因此,这种非侵入性技术在疲劳监测和恢复平准方面很有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
European Journal of Human Movement
European Journal of Human Movement Social Sciences-Social Sciences (miscellaneous)
CiteScore
0.90
自引率
0.00%
发文量
0
审稿时长
5 weeks
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