Feuser Ann-Kristin, Gesell-May Stefan, Müller Tobias, May Anna
Equine Hospital in Parsdorf, 85599 Vaterstetten, Germany.
Anirec GmbH, Artificial Intelligence Solutions in Veterinary Medicine, 80539 Munich, Germany.
Animals (Basel). 2022 Oct 17;12(20):2804. doi: 10.3390/ani12202804.
Lameness in horses is a long-known issue influencing the welfare, as well as the use, of a horse. Nevertheless, the detection and classification of lameness mainly occurs on a subjective basis by the owner and the veterinarian. The aim of this study was the development of a lameness detection system based on pose estimation, which permits non-invasive and easily applicable gait analysis. The use of 58 reference points on easily detectable anatomical landmarks offers various possibilities for gait evaluation using a simple setup. For this study, three groups of horses were used: one training group, one analysis group of fore and hindlimb lame horses and a control group of sound horses. The first group was used to train the network; afterwards, horses with and without lameness were evaluated. The results show that forelimb lameness can be detected by visualising the trajectories of the reference points on the head and both forelimbs. In hindlimb lameness, the stifle showed promising results as a reference point, whereas the tuber coxae were deemed unsuitable as a reference point. The study presents a feasible application of pose estimation for lameness detection, but further development using a larger dataset is essential.
马匹跛行是一个长期存在的问题，会影响马匹的健康和使用。然而，跛行的检测和分类主要由马主和兽医主观进行。本研究的目的是开发一种基于姿态估计的跛行检测系统，该系统允许进行非侵入性且易于应用的步态分析。在易于检测的解剖标志点上使用58个参考点，通过简单的设置为步态评估提供了多种可能性。本研究使用了三组马匹：一组训练组、一组前肢和后肢跛行马的分析组以及一组健康马的对照组。第一组用于训练网络；之后，对有跛行和无跛行的马匹进行评估。结果表明，通过可视化头部和两个前肢上参考点的轨迹可以检测前肢跛行。在后肢跛行中，膝关节作为参考点显示出有希望的结果，而髋结节被认为不适合作参考点。该研究提出了姿态估计在跛行检测中的可行应用，但使用更大的数据集进行进一步开发至关重要。
