Haimovich Yaron, Hershkovich Oded, Portnoy Sigal, Schwartz Isabella, Lotan Raphael
Orthopedic Surgery Department, Wolfson Medical Center, Holon, Israel.
Department of Physical Medicine and Rehabilitation, Hadassah Medical Center, Jerusalem, Israel.
Physiother Can. 2021 Nov 1;73(4):391-400. doi: 10.3138/ptc-2020-0051. Epub 2021 Oct 20.
Our aim was to evaluate the Microsoft Kinect sensor (MKS) as a markerless system for motion capture and analysis of lower limb motion, compare it with a state-of-the-art marker-based system (MBS), and investigate its accuracy in simultaneously capturing several lower limb joint movements on several planes while participants walked freely. Participants were asked to walk while gait data were simultaneously recorded by both the MKS and the MBS. Software for analysing the Kinect data stream was developed using Microsoft Visual Studio and Kinect for Windows software development kits. Visual three-dimensional (3D) C-Motion software was used to calculate 3D joint angles of the MBS. Deviation of the joint angles calculated by the two systems was calculated using root-mean-square error (RMSE) on the basis of a designated formula. The calculated RMSE average was <5° between the two systems, a level of difference that has practically no clinical significance. Quantitative measurements of the joint angles of the knee and hip can be acquired using one MKS with some accuracy. The system can be advantageous for clinical use, at the pre- and post-treatment stages of rehabilitation, at significantly lower costs. Further evaluation of the MKS should be performed with larger study populations.
我们的目的是评估微软Kinect传感器(MKS)作为一种用于下肢运动捕捉和分析的无标记系统,将其与先进的基于标记的系统(MBS)进行比较,并研究其在参与者自由行走时同时捕捉多个平面上的多个下肢关节运动的准确性。要求参与者行走,同时MKS和MBS记录步态数据。使用Microsoft Visual Studio和Kinect for Windows软件开发工具包开发了用于分析Kinect数据流的软件。使用Visual三维(3D)C-Motion软件计算MBS的3D关节角度。根据指定公式,使用均方根误差(RMSE)计算两个系统计算的关节角度偏差。两个系统之间计算出的RMSE平均值<5°,这种差异水平在临床上几乎没有意义。使用一个MKS可以获得一定精度的膝关节和髋关节关节角度的定量测量。该系统在康复治疗的前后阶段,以显著更低的成本用于临床可能具有优势。应使用更大的研究人群对MKS进行进一步评估。