Riazati Sherveen, McGuirk Theresa E, Perry Elliott S, Sihanath Wandasun B, Patten Carolynn
Biomechanics, Rehabilitation, and Integrative Neuroscience Lab, Department of Physical Medicine and Rehabilitation, School of Medicine, University of California, Davis, Sacramento, CA, United States.
UC Davis Healthy Aging in a Digital World Initiative, a UC Davis "Big Idea", Sacramento, CA, United States.
Front Hum Neurosci. 2022 Jun 16;16:867474. doi: 10.3389/fnhum.2022.867474. eCollection 2022.
: To examine the between-day absolute reliability of gait parameters acquired with Theia3D markerless motion capture for use in biomechanical and clinical settings. : Twenty-one (7 M,14 F) participants aged between 18 and 73 years were recruited in community locations to perform two walking tasks: self-selected and fastest-comfortable walking speed. Participants walked along a designated walkway on two separate days.Joint angle kinematics for the hip, knee, and ankle, for all planes of motion, and spatiotemporal parameters were extracted to determine absolute reliability between-days. For kinematics, absolute reliability was examined using: full curve analysis [root mean square difference (RMSD)] and discrete point analysis at defined gait events using standard error of measurement (SEM). The absolute reliability of spatiotemporal parameters was also examined using SEM and SEM%. : Markerless motion capture produced low measurement error for kinematic full curve analysis with RMSDs ranging between 0.96° and 3.71° across all joints and planes for both walking tasks. Similarly, discrete point analysis within the gait cycle produced SEM values ranging between 0.91° and 3.25° for both sagittal and frontal plane angles of the hip, knee, and ankle. The highest measurement errors were observed in the transverse plane, with SEM >5° for ankle and knee range of motion. For the majority of spatiotemporal parameters, markerless motion capture produced low SEM values and SEM% below 10%. : Markerless motion capture using Theia3D offers reliable gait analysis suitable for biomechanical and clinical use.
研究使用Theia3D无标记运动捕捉系统获取的步态参数在日间的绝对可靠性,以用于生物力学和临床环境。
招募了21名年龄在18至73岁之间的参与者(7名男性,14名女性),在社区场所进行两项步行任务:自选步行速度和最快舒适步行速度。参与者在两个不同的日子沿着指定的走道行走。提取髋、膝和踝关节在所有运动平面的关节角运动学以及时空参数,以确定日间的绝对可靠性。对于运动学,使用以下方法检查绝对可靠性:全曲线分析[均方根差(RMSD)]以及在定义的步态事件处使用测量标准误差(SEM)进行离散点分析。时空参数的绝对可靠性也使用SEM和SEM%进行检查。
无标记运动捕捉系统在运动学全曲线分析中产生的测量误差较低,两项步行任务中所有关节和平面的RMSD范围在0.96°至3.71°之间。同样,步态周期内的离散点分析显示,髋、膝和踝关节矢状面和额状面角度的SEM值范围在0.91°至3.25°之间。在横断面观察到最高的测量误差,踝关节和膝关节运动范围的SEM>5°。对于大多数时空参数,无标记运动捕捉系统产生的SEM值较低,且SEM%低于10%。
使用Theia3D的无标记运动捕捉系统提供了适用于生物力学和临床应用的可靠步态分析。