Suppr超能文献

数字视频分析揭示了步态参数,这些参数可以预测三日赛跳跃测试阶段的表现。

Digital video analysis reveals gait parameters that predict performance in the jumping test phase of three-day eventing.

机构信息

University of Florida Department of Animal Sciences, 2250 Shealy Dr, Gainesville, FL, 32608.

University of Florida Department of Biomedical Sciences, 1275 Center Dr, Gainesville, FL, 32611.

出版信息

J Equine Vet Sci. 2024 Oct;141:105166. doi: 10.1016/j.jevs.2024.105166. Epub 2024 Aug 17.

Abstract

In international equestrian sport, visual inspections assess gait and lameness to protect the welfare of performance horses during competition. Horses competing internationally in three-day eventing must pass two mandatory inspections (pre-competition and post-cross country) before attempting the final phase: the jumping test (JT). We hypothesized that digitally quantifying objective gait parameters captured during the two mandatory inspections will identify locomotor characteristics that predict success during the jumping test. Utilizing the DeepLabCut (DLC) software package for labeling of anatomical landmarks and a custom analysis pipeline we calculated gait parameters for 194 competition horses at the trot. During the pre-competition inspection, relative trot speed was significantly associated (P = 0.0060, GLMM), and the forelimb travel trended towards significance (P =0.0800, GLMM), with achieving a clear round in the later jumping test. Post-cross country, the forelimb travel significantly predicted JT results (P = 0.0188, GLMM). As our parameters are scaled for body size, these parameters may indicate conformational characteristics for superior jumping ability and overall athletic fitness. Within each competitive effort, comparisons of the post-cross country and pre-competition observations revealed that the change in speed and duty factor were significantly different in the group that accrued jumping faults (P = 0.00376 and P = 0.02430, GLMM), perhaps capturing locomotor signs of exercise fatigue. Further work employing these approaches to better understand competition performance will encourage the use of objective measures to protect sport horse welfare, as well as provide an advantageous tool for gait evaluation in the horse.

摘要

在国际马术运动中,视觉检查评估步态和跛行,以保护比赛中表演马的福利。参加三日赛的国际比赛的马匹必须通过两次强制性检查(比赛前和越野赛后),然后才能尝试最后一个阶段:跳跃测试(JT)。我们假设在两次强制性检查期间数字化量化客观的步态参数,将确定预测跳跃测试成功的运动特征。利用 DeepLabCut(DLC)软件包进行解剖标志的标记和自定义分析管道,我们计算了 194 匹比赛马在小跑时的步态参数。在比赛前的检查中,相对小跑速度与(P=0.0060,GLMM)显著相关,前肢运动也有显著趋势(P=0.0800,GLMM),在稍后的跳跃测试中取得了清晰的一轮。越野赛后,前肢运动显著预测了 JT 的结果(P=0.0188,GLMM)。由于我们的参数是按体型缩放的,这些参数可能表明了优越跳跃能力和整体运动适应性的形态特征。在每一次竞争中,对越野赛后和比赛前的观察结果进行比较,发现积累跳跃失误的组的速度和功重比变化有显著差异(P=0.00376 和 P=0.02430,GLMM),这可能捕捉到运动疲劳的运动迹象。进一步采用这些方法来更好地了解比赛表现的工作将鼓励使用客观措施来保护运动马的福利,并为马的步态评估提供有利的工具。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验