Kinect-Based Knee Osteoarthritis Gait Analysis System

Ivan Yong-Sing Lau, T. Chua, W. Lee, Chya-Wei Wong, T. Toh, H. Ting
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Abstract

Measurement of the gait parameter typically requires a combination of force plate and motion tracking system, which restricts the calculated value to the laboratory environment. The possibility of a portable tracking system has been investigated in some recent studies, such as Microsoft Kinect sensors. The present research collaborated with Sibu Hospital and KPJ Sibu Specialist Hospital to collect the data from subjects. Concurrently, the law of cosine and dot cross product was used as primary measures to determine the scalar value of vector knee, ankle, and hip and the angle that formed by knee, ankle, and hip. The result generated by the proposed knee osteoarthritis severity diagnostics system is presented, specifically, demonstrate the analysis algorithm of various gait parameters system. In summary, Microsoft Kinect v2 sensor can be utilised in the present research to capture subject movement, and a knee osteoarthritis severity diagnostics system is proposed as clinically feasible options for gait analysis.
基于运动学的膝关节骨关节炎步态分析系统
步态参数的测量通常需要结合测力板和运动跟踪系统,这将计算值限制在实验室环境中。最近的一些研究已经对便携式跟踪系统的可能性进行了调查,比如微软的Kinect传感器。本研究与泗巫医院及KPJ泗巫专科医院合作收集被试资料。同时,利用余弦定律和点叉积定律作为主要测度,确定了向量膝盖、脚踝、臀部的标量值以及膝盖、脚踝、臀部形成的角度。给出了所提出的膝关节骨关节炎严重程度诊断系统生成的结果,具体演示了各种步态参数系统的分析算法。综上所述,微软Kinect v2传感器可用于本研究中捕捉受试者的运动,并提出膝关节骨关节炎严重程度诊断系统作为临床可行的步态分析选择。
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