赛马运动中的步态分析

J. Echterhoff, Juan Haladjian, B. Brügge
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引用次数: 6

摘要

在现代障碍赛和越野马术比赛中,一对骑手必须在规定的时间内跳过一系列障碍。如果一匹马能够轻松地跳过栅栏,栅栏的任何部分都不会掉下来,那么这一次跳跃就被认为是成功的(没有惩罚)。如果栅栏的任何部分倒下或马匹拒绝跳跃,骑手将被扣分或被取消比赛资格。一次不成功的跳跃会导致受伤和失去对骑手的信任。成功的跳跃是由马在栅栏前跨步的次数、长度和和谐度决定的。我们提出了一个系统,可以使用连接在马鞍上的智能手机来跟踪马的跨步和跳跃。我们的系统检测和分割单个步幅,并使用信号处理和机器学习方法计算步幅的长度。我们收集了9匹马的数据,这些马进行了几次跳跃。我们的结果表明,我们的系统可以检测到精度为96.3%的马跨步,召回率为95.7%,pearson相关性为0.73。我们进一步描述了一种表征马的慢跑步态的方法。我们的系统旨在供骑手使用,以适应他们的训练和比赛策略,以适应马的身体限制。因此,骑手可以防止事故,由于过度负担的马或错误的计算中心跨步的骑手。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Gait analysis in horse sports
In modern showjumping and cross-country riding, horse-rider-pairs have to jump a series of obstacles in a given time. A jump is considered successful (penalty-free) if a horse can comfortably jump the fence without elements of the fence falling down. If any of the elements of the fence falls down or the horse refuses to jump, the rider obtains penalty points or can be disqualified from the competition. An unsuccessful jump can lead to injury and loss in trust of the rider. The success of a jump is determined by the number, length and harmony of strides a horse performs before a fence. We propose a system for tracking horse strides and jumps using a smartphone attached to the horse's saddle. Our system detects and segments individual strides and computes the length of a stride using signal processing and machine learning methods. We collected data from 9 horses who performed several jumps. Our results indicate that our system can detect horse strides with a precision of 96.3%, a recall of 95.7% and a pearson correlation of 0.73 with respect to our ground truth data set. We further describe a method to characterise the canter gait of the horse. Our system is intended to be used by riders to adapt their training and competition strategies to the physical limitations of the horse. The rider can thus prevent accidents due to an overtaxing of the horse or miscalculation of canter strides by the rider.
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