Bragança F M, Bosch S, Voskamp J P, Marin-Perianu M, Van der Zwaag B J, Vernooij J C M, van Weeren P R, Back W
Department of Equine Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands.
Inertia Technology B.V., Enschede, the Netherlands.
Equine Vet J. 2017 Jul;49(4):545-551. doi: 10.1111/evj.12651. Epub 2016 Dec 13.
Inertial measurement unit (IMU) sensor-based techniques are becoming more popular in horses as a tool for objective locomotor assessment.
To describe, evaluate and validate a method of stride detection and quantification at walk and trot using distal limb mounted IMU sensors.
Prospective validation study comparing IMU sensors and motion capture with force plate data.
A total of seven Warmblood horses equipped with metacarpal/metatarsal IMU sensors and reflective markers for motion capture were hand walked and trotted over a force plate. Using four custom built algorithms hoof-on/hoof-off timing over the force plate were calculated for each trial from the IMU data. Accuracy of the computed parameters was calculated as the mean difference in milliseconds between the IMU or motion capture generated data and the data from the force plate, precision as the s.d. of these differences and percentage of error with accuracy of the calculated parameter as a percentage of the force plate stance duration.
Accuracy, precision and percentage of error of the best performing IMU algorithm for stance duration at walk were 28.5, 31.6 ms and 3.7% for the forelimbs and -5.5, 20.1 ms and -0.8% for the hindlimbs, respectively. At trot the best performing algorithm achieved accuracy, precision and percentage of error of -27.6/8.8 ms/-8.4% for the forelimbs and 6.3/33.5 ms/9.1% for the hindlimbs.
The described algorithms have not been assessed on different surfaces.
Inertial measurement unit technology can be used to determine temporal kinematic stride variables at walk and trot justifying its use in gait and performance analysis. However, precision of the method may not be sufficient to detect all possible lameness-related changes. These data seem promising enough to warrant further research to evaluate whether this approach will be useful for appraising the majority of clinically relevant gait changes encountered in practice.
基于惯性测量单元(IMU)传感器的技术在马匹中作为客观运动评估工具正变得越来越流行。
描述、评估和验证一种使用安装在肢体远端的IMU传感器在行走和小跑时进行步幅检测和量化的方法。
将IMU传感器和运动捕捉与测力板数据进行比较的前瞻性验证研究。
总共七匹温血马配备了掌骨/跖骨IMU传感器和用于运动捕捉的反光标记,牵它们在测力板上行走和小跑。使用四种定制算法,从IMU数据中计算每次试验在测力板上的蹄触地/离地时间。计算所得参数的准确性为IMU或运动捕捉生成的数据与测力板数据之间以毫秒为单位的平均差异,精确性为这些差异的标准差,误差百分比为计算参数的准确性占测力板站立持续时间的百分比。
行走时,前肢最佳性能的IMU算法在站立持续时间方面的准确性、精确性和误差百分比分别为28.5、31.6毫秒和3.7%,后肢分别为-5.5、20.1毫秒和-0.8%。小跑时,最佳性能算法在前肢的准确性、精确性和误差百分比为-27.6/8.8毫秒/-8.4%,后肢为6.3/33.5毫秒/9.1%。
所描述的算法尚未在不同表面上进行评估。
惯性测量单元技术可用于确定行走和小跑时的时间运动学步幅变量,证明其在步态和性能分析中的应用价值。然而,该方法的精确性可能不足以检测所有可能与跛行相关的变化。这些数据似乎很有前景,足以保证进一步研究,以评估这种方法是否有助于评估实践中遇到的大多数临床相关步态变化。