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A step in the right direction: an open-design pedometer algorithm for dogs

机译:朝正确方向迈出的一步:针对狗的开放式计步器算法

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摘要

BackgroundAccelerometer-based technologies could be useful in providing objective measures of canine ambulation, but most are either not tailored to the idiosyncrasies of canine gait, or, use un-validated or closed source approaches. The aim of this paper was to validate algorithms which could be applied to accelerometer data for i) counting the number of steps and ii) distance travelled by a dog.To count steps, an approach based on partitioning acceleration was used. This was applied to accelerometer data from 13 dogs which were walked a set distance and filmed. Each footfall captured on video was annotated. In a second experiment, an approach based on signal features was used to estimate distance travelled. This was applied to accelerometer data from 10 dogs with osteoarthritis during normal walks with their owners where GPS (Global Positioning System) was also captured. Pearson’s correlations and Bland Altman statistics were used to compare i) the number of steps measured on video footage and predicted by the algorithm and ii) the distance travelled estimated by GPS and predicted by the algorithm.
机译:背景技术基于加速度计的技术可用于提供犬行走的客观测量,但是大多数要么不是针对犬步态的特质量身定制的,要么使用未经验证或封闭的方法。本文旨在验证可用于加速度计数据的算法,用于i)计算步数和ii)狗的行进距离。要计算步数,使用了基于分区加速度的方法。将其应用于来自13只狗的加速计数据,这些狗走了一段距离并进行了拍摄。记录在视频上的每个脚步都有注释。在第二个实验中,基于信号特征的方法被用来估计行进距离。该数据已应用于10只患有骨关节炎的狗在与主人的正常行走过程中的加速度计数据,其中还捕获了GPS(全球定位系统)。皮尔逊的相关性和布兰德·奥特曼(Bland Altman)统计数据用于比较i)在视频镜头上测量并通过算法预测的步数,以及ii)GPS估算并通过算法预测的行进距离。

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