基于Kinect系统的步态参数提取方法
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杭州电子科技大学机械工程学院,杭州310018

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浙江省重点研发计划(2017C03040)。


Extraction Method of Gait Parameters Based on Kinect System
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School of Mechanical Engineering, Hangzhou Dianzi University,Hangzhou 310018, China

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    摘要:

    基于步态参数的定义,研究并提出了使用微软最新一代Azure Kinect无标记运动捕获系统(以下简称Kinect系统)采集并提取步态参数的方法,同时在数据处理中分别采用自适应滤波、指数滤波、卡尔曼滤波及无滤波条件,以提高步态参数计算结果的准确性与可靠性。为了评价本文计算方法的准确性与滤波效果,将提取的步态参数结果与同步实验的Qualisys标记式运动捕获系统(瑞典Qualisys公司,简称Q标记法)的结果进行统计学对比分析,并据此对不同滤波方法进行评价。结果显示,总体而言Kinect系统与Q标记法的结果一致性较高,结果均落在95%一致性界限内,并且在有滤波条件下的准确度要高于无滤波条件,且卡尔曼滤波的效果最好;在单个步态参数方面,步速的结果在所有滤波条件下均有较大差异性,无法应用;对于其他参数,本文方法表现了较高的准确性与一致性,并且应用卡尔曼滤波后的一致性与可靠性都有所提高。应用本文方法并使用卡尔曼滤波进行平滑处理后,Kinect系统可以较为准确地计算健康人的步态参数,并在某些情况下代替标记法设备。

    Abstract:

    Based on the definition of gait parameters, this paper proposes and studies a method of collecting and extracting gait parameters using the Microsoft’s Azure Kinect maker-free motion capture system(hereinafter referred to as Kinect system). At the same time, adaptive filtering, exponential filtering, Kalman filtering and no filtering conditions are used in data processing to improve the smoothness of gait data. In order to evaluate the accuracy of Kinect system and the effectiveness of filtering, the results of extracted gait parameter are statistically compared with those of the Qualisys marker-based motion capture system (Company of Sweden, hereinafter referred to as Q marker-based) in the synchronous experiment, and the different filtering methods are evaluated accordingly. The results show that, in general, the Kinect system has a high consistency with the Q marker-based, and the results under the three filtering conditions all fall within the 95% consistency limit. In terms of their gait parameters, the results of the gait speed are quite different under all filtering conditions, which cannot be applied. For other parameters, adaptive filtering and Kalman filtering show good consistency. Kinect system can accurately calculate the gait parameters of healthy people by applying the proposed method and smoothing it with Kalman filtering, and it can replace the marker-based device in some cases.

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张笑宇,陈凯,杨颖.基于Kinect系统的步态参数提取方法[J].数据采集与处理,2022,37(4):872-882

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  • 收稿日期:2021-11-01
  • 最后修改日期:2022-07-11
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  • 在线发布日期: 2022-08-11