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一种无标记运动捕捉系统在平地和跑步机上行走时测量躯干、髋部和膝部角度的可靠性。

Reliability of a markerless motion capture system to measure the trunk, hip and knee angle during walking on a flatland and a treadmill.

作者信息

Tamura Hiroyuki, Tanaka Ryo, Kawanishi Hiromichi

机构信息

Department of Rehabilitation, Hiroshima International University, Hiroshima, Japan.

Graduate School of Humanities and Social Sciences, Hiroshima University, Hiroshima, Japan; Department of Rehabilitation, Hiroshima International University, Hiroshima, Japan.

出版信息

J Biomech. 2020 Aug 26;109:109929. doi: 10.1016/j.jbiomech.2020.109929. Epub 2020 Jul 1.

Abstract

Markerless motion capture system (MLS) using an infrared sensor such as Microsoft Kinect has been used for gait analysis. Several studies have shown that kinematic measurements of trunk and lower limb joint angles during walking measured by MLS are valid. However, the reproducibility, presence of systematic error, or degree of random error of kinematic measurements during walking using MLS with Kinect v2 were not demonstrated. This study was made to confirm the reliability of kinematic measurements using Kinect v2 during gait. Twenty-two young, injury-free individuals volunteered to participate. Walks were made at 2 miles per hour (mph) on both the flatland and the treadmill. Intra-class correlation coefficients (ICCs) were calculated, systematic errors identified, and minimal detectable changes (MDCs) were estimated to assess the reliability of kinematic measurements of trunk, hip, and knee joint angles during walking. For trunk angles measured on the flatland, ICC was higher than 0.6, systematic error was smaller, and MDC was 2.2° smaller than that in gait on the treadmill (6.6°). In hip joint angles measured on the flatland, although systematic error was slight, ICC was not higher than on the treadmill and MDC exceeded 5°. The results for the knee joint were similar to those of the hip joint. Kinect can detect kinematic abnormalities of the trunk during slow walking on the flatland easier than on the treadmill.

摘要

使用诸如微软Kinect等红外传感器的无标记运动捕捉系统(MLS)已被用于步态分析。多项研究表明,通过MLS测量的步行过程中躯干和下肢关节角度的运动学测量是有效的。然而,使用Kinect v2的MLS在步行过程中运动学测量的可重复性、系统误差的存在或随机误差的程度尚未得到证实。本研究旨在确认使用Kinect v2在步态期间进行运动学测量的可靠性。22名无损伤的年轻个体自愿参与。在平地和跑步机上均以每小时2英里(mph)的速度行走。计算组内相关系数(ICC),识别系统误差,并估计最小可检测变化(MDC),以评估步行过程中躯干、髋部和膝关节角度运动学测量的可靠性。对于在平地上测量的躯干角度,ICC高于0.6,系统误差较小,且MDC比在跑步机上的步态测量值小2.2°(6.6°)。对于在平地上测量的髋关节角度,尽管系统误差较小,但ICC不高于在跑步机上的测量值,且MDC超过5°。膝关节的结果与髋关节相似。与在跑步机上相比,Kinect在平地上慢走时更容易检测到躯干的运动学异常。

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