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使用单只足部佩戴的惯性测量单元测定地面跑步时的步幅长度。

Stride length determination during overground running using a single foot-mounted inertial measurement unit.

作者信息

Brahms C Markus, Zhao Yang, Gerhard David, Barden John M

机构信息

Faculty of Kinesiology and Health Studies, University of Regina, Canada.

Faculty of Science, Department of Computer Science, University of Regina, Canada.

出版信息

J Biomech. 2018 Apr 11;71:302-305. doi: 10.1016/j.jbiomech.2018.02.003. Epub 2018 Feb 10.

Abstract

From a research perspective, detailed knowledge about stride length (SL) is important for coaches, clinicians and researchers because together with stride rate it determines the speed of locomotion. Moreover, individual SL vectors represent the integrated output of different biomechanical determinants and as such provide valuable insight into the control of running gait. In recent years, several studies have tried to estimate SL using body-mounted inertial measurement units (IMUs) and have reported promising results. However, many studies have used systems based on multiple sensors or have only focused on estimating SL for walking. Here we test the concurrent validity of a single foot-mounted, 9-degree of freedom IMU to estimate SL for running. We employed a running-specific, Kalman filter based zero-velocity update (ZUPT) algorithm to calculate individual SL vectors with the IMU and compared the results to SLs that were simultaneously recorded by a 6-camera 3D motion capture system. The results showed that the analytical procedures were able to successfully identify all strides that were recorded by the camera system and that excellent levels of absolute agreement (ICC(3,1) = 0.955) existed between the two methods. The findings demonstrate that individual SL vectors can be accurately estimated with a single foot-mounted IMU when running in a controlled laboratory setting.

摘要

从研究角度来看,详细了解步长(SL)对教练、临床医生和研究人员都很重要,因为它与步频共同决定了运动速度。此外,个体的SL向量代表了不同生物力学决定因素的综合输出,因此能为跑步步态控制提供有价值的见解。近年来,多项研究尝试使用佩戴在身体上的惯性测量单元(IMU)来估计步长,并取得了令人鼓舞的结果。然而,许多研究使用的是基于多个传感器的系统,或者仅专注于估计步行的步长。在此,我们测试了一种单只脚佩戴的、9自由度IMU估计跑步步长的同时效度。我们采用了一种基于卡尔曼滤波器的、针对跑步的零速度更新(ZUPT)算法,利用IMU计算个体的SL向量,并将结果与由一个6摄像头3D运动捕捉系统同时记录的步长进行比较。结果表明,分析程序能够成功识别摄像头系统记录的所有步幅,且两种方法之间存在高度的绝对一致性(组内相关系数ICC(3,1) = 0.955)。这些发现表明,在受控的实验室环境中跑步时,使用单只脚佩戴的IMU能够准确估计个体的SL向量。

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