Keegan Kevin G, Yonezawa Yoshiharu, Pai P Frank, Wilson David A
Department of Veterinary Medicine and Surgery, College of Veterinary Medicine, University of Missouri, Columbia, MO 65211, USA.
Biomed Sci Instrum. 2002;38:107-12.
Video-based kinematic analysis of gait in horses is accurate for quantification of lameness and reliable for identification of the affected limb. Algorithms for the measurement of the vertical head and pelvic displacement and phase correlation with vertical displacement of one forelimb and hindlimb foot have been developed for this purpose. However, because of camera field-of-view limitations, video-based analysis of gait can only be reliably accomplished with the horse constrained to move on a treadmill. This paper describes the use of 2 single-axis accelerometers and 2 gyroscopic transducers as a measurement system for the identification and quantification of forelimb and hindlimb lameness in horses. Vertical head and pelvic acceleration are converted to displacement, lameness is quantified from previously developed algorithms, and affected limb is determined by correlation of head and pelvic signals with gyroscopic signals from the right forelimb and hindlimb feet. Signals from the 4 transducers are telemeterized at 200 Hz and collected to a receiver connected to a lap top computer, freeing the horse from the constraints of a treadmill laboratory setting. In this paper we describe the reliability of this new accelerometer-based system in horses with induced lameness while trotting on a treadmill and freely outside overground.
基于视频的马匹步态运动学分析在跛行量化方面准确，在确定患肢方面可靠。为此已开发出测量头部垂直位移、骨盆位移以及与一个前肢和后肢足部垂直位移的相位相关性的算法。然而，由于相机视野限制，基于视频的步态分析只有在马匹被限制在跑步机上移动时才能可靠完成。本文描述了使用2个单轴加速度计和2个陀螺仪传感器作为测量系统来识别和量化马匹前肢和后肢跛行。将头部和骨盆的垂直加速度转换为位移，根据先前开发的算法对跛行进行量化，并通过将头部和骨盆信号与右前肢和后肢足部的陀螺仪信号进行关联来确定患肢。来自4个传感器的信号以200赫兹进行遥测，并收集到连接到笔记本电脑的接收器中，使马匹摆脱了跑步机实验室环境的限制。在本文中，我们描述了这种基于加速度计的新系统在诱导跛行的马匹在跑步机上小跑以及在户外自由行走时的可靠性。
