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使用ANALOC-E进行定量分析所展示的四种马步态类别的变化。

Variation in Four Horse Gait Categories Illustrated by Quantitative Analysis With ANALOC-E.

作者信息

Staiger Elizabeth Ann, Pereira de Toledo Adalton, Rizzato Paschoal Victoria, Patterson Rosa Laura

机构信息

Department of Animal Science & Veterinary Technology, Texas A&M University, Kingsville, Texas, USA.

Toledo Horse, São Paulo, São Paulo, Brazil.

出版信息

Vet Med Int. 2025 Aug 6;2025:4906015. doi: 10.1155/vmi/4906015. eCollection 2025.

Abstract

Horse gaits are a trait highly selected and prized in diverse breeds. Meanwhile, gait classification relies mostly on subjective visual observations by evaluators. Noninvasive equipment able to track locomotion in horses and output quantitative gait parameters is not only helpful in evaluating locomotion but also in designating gait types and its variations. Equine locomotion pattern designation based solely on observer evaluation can be subjective; therefore, utilizing tools that provide quantitative results and track individual limb movements, especially during intermediate-speed gaits, can result in increased phenotypic accuracy and better designation. A noninvasive automated locomotion analysis system (ANALOC-E) was used to acquire locomotion parameters in a small yet diverse set of 68 horses of 4 breeds. We aimed to evaluate kinematic variation in horse locomotion patterns for these 68 horses. Analysis demonstrates kinematic variation within breed-designated gaits. We also compared output parameters to previously described standards, as well as assessed principal component scores within the dataset. We illustrate two gait types not described by the previous standards (marcha de centro and marcha trotada) yet recognized by breed designations. Three parameters (lateral support, diagonal support, and triple support) can explain about 98.9% of the variance in gait types in this dataset. Results suggest that ANALOC-E could be used for locomotion analysis, but further validation is necessary to evaluate the accuracy of the system. Noninvasive technologies that encourage natural locomotion and output quantitative biomechanical/kinematic parameters may assist in real-time, accurate, locomotion descriptions.

摘要

马的步态是一个在不同品种中经过高度选择和珍视的特征。与此同时,步态分类主要依赖于评估者的主观视觉观察。能够跟踪马的运动并输出定量步态参数的非侵入性设备不仅有助于评估运动,还有助于确定步态类型及其变化。仅基于观察者评估来确定马的运动模式可能具有主观性;因此,使用能够提供定量结果并跟踪单个肢体运动的工具,尤其是在中等速度步态期间,可以提高表型准确性并实现更好的分类。使用一种非侵入性自动运动分析系统(ANALOC-E)在一小群但品种多样的68匹马(分属4个品种)中获取运动参数。我们旨在评估这68匹马的运动模式中的运动学变化。分析表明在品种指定的步态内存在运动学变化。我们还将输出参数与先前描述的标准进行了比较,并评估了数据集中的主成分得分。我们展示了两种先前标准未描述但被品种分类所认可的步态类型(marcha de centro和marcha trotada)。三个参数(侧向支撑、对角支撑和三联支撑)可以解释该数据集中步态类型约98.9%的方差。结果表明ANALOC-E可用于运动分析,但需要进一步验证以评估该系统的准确性。鼓励自然运动并输出定量生物力学/运动学参数的非侵入性技术可能有助于进行实时、准确的运动描述。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/80f0/12349990/385ef76b0aab/VMI2025-4906015.001.jpg

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