Eager David, Hossain Imam, Ishac Karlos, Robins Scott
Faculty of Engineering and Information Technology, University of Technology Sydney, P.O. Box 123, Broadway, NSW 2007, Australia.
Greyhound Racing Victoria, 46-50 Chetwynd Street, West Melbourne, VIC 3003, Australia.
Animals (Basel). 2021 Sep 14;11(9):2687. doi: 10.3390/ani11092687.
The University of Technology Sydney (UTS) has been working closely with the Australasian greyhound industry for more than 5 years to reduce greyhound race-related injuries. During this period, UTS has developed and deployed several different techniques including inertial measurement units, drones, high-frame-rate cameras, track geometric surveys, paw print analysis, track soil spring-force analysis, track maintenance data, race injury data, race computer simulation and modelling to assist in this task. During the period where the UTS recommendations have been adopted, the injury rate has dropped significantly. This has been achieved by animal welfare interventions that lower racing congestion, and lower transient forces and jerk rates the greyhounds experience during a race. This study investigated the use of a greyhound location tracing system where small and lightweight signal emitting devices were placed inside a pocket in the jackets of racing greyhounds. The system deployed an enhanced version of a player tracking system currently used to track the motion of human athletes. Greyhounds gallop at speeds of almost 20 m/s and are known to change their heading direction to exceed a yaw rate of 0.4 rad/s. The high magnitudes of velocity, acceleration and jerk posed significant technical challenges, as the greyhounds pushed the human tracking system beyond its original design limits. Clean race data gathered over a six-month period were analysed and presented for a typical 2-turn greyhound racing track. The data confirmed that on average, greyhounds ran along a path that resulted in the least energy wastage, which includes smooth non-linear paths that resemble easement curves at the transition between the straights to the semi-circular bends. This study also verified that the maximum jerk levels greyhounds experienced while racing were lower than the jerk levels that had been predicted with simulations and modelling for the track path. Furthermore, the results from this study show the possibility of such a systems deployment in data gathering in similar settings to greyhound racing such as thoroughbred and harness horse racing for understanding biomechanical kinematic performance.
悉尼科技大学（UTS）已与澳大利亚灰狗行业密切合作超过5年，以减少与灰狗赛跑相关的伤害。在此期间，悉尼科技大学开发并应用了多种不同技术，包括惯性测量单元、无人机、高帧率摄像机、赛道几何测量、爪印分析、赛道土壤弹力分析、赛道维护数据、比赛伤害数据、比赛计算机模拟和建模，以协助完成这项任务。在采用悉尼科技大学建议的期间，受伤率显著下降。这是通过动物福利干预措施实现的，这些措施减少了比赛拥堵，并降低了灰狗在比赛中所经历的瞬态力和急动率。本研究调查了一种灰狗位置追踪系统的使用情况，该系统将小型轻便的信号发射装置放置在参赛灰狗夹克的口袋内。该系统采用了目前用于追踪人类运动员运动的运动员追踪系统的增强版本。灰狗奔跑速度接近20米/秒，并且已知它们会改变前进方向，偏航率超过0.4弧度/秒。由于灰狗将人类追踪系统推到了其原始设计极限之外，高速度、加速度和急动度带来了重大技术挑战。对在六个月期间收集的纯净比赛数据进行了分析，并针对典型的两圈灰狗赛道进行了展示。数据证实，平均而言，灰狗沿着能量浪费最少的路径奔跑，其中包括在直道与半圆形弯道过渡处类似缓和曲线的平滑非线性路径。本研究还验证了灰狗在比赛中所经历的最大急动水平低于针对赛道路径通过模拟和建模预测的急动水平。此外，本研究结果表明，这种系统有可能部署在与灰狗赛跑类似的环境中进行数据收集，例如纯种马和挽马赛跑，以了解生物力学运动学性能。
