人类运动的动态系统理论,通过使用Kinect的角度图探索协调模式

John Edison Muñoz Cardona, J. F. Villada, S. Casanova, Maria Fernanda Montoya Vega, Ó. Henao
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引用次数: 3

摘要

使用线性空间/角度运动学分析时间序列数据,传统上使用低成本相机(如Kinect传感器)来量化人体运动。这种传统方法难以分析人体关节间的相互作用,且协调参数隐藏。动态系统理论(DST)提供了一个非线性的框架来分析人体运动,通过表示在角-角图之间的相互作用。DST为研究人体运动的协调性提供了精确的解决方案,但它也需要昂贵的硬件和非常专业的生物力学软件。本文描述了用Kinect传感器记录的运动数据进行DST分析的方法学程序。具体来说,我们解决了创建和解释角度图的问题,重点是探索运动捕捉(MoCap)信号中的协调模式。我们介绍了一种促进DST分析的方法,并将其应用于真实场景中人体运动分析的两个不同用例:运动手势研究和身体康复干预中的运动分析。结果表明,当需要考虑两个关节时,从角度图中可以推导出重要的协调参数,提高了对运动数据的理解。因此,我们证明了DST分析可以用便宜的工具进行,为新的健康严肃游戏中的协调和运动同步分析提供了一种有希望的方法。
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Dynamic Systems Theory in Human Movement Exploring Coordination Patterns by Angle-Angle Diagrams Using Kinect
Analyzing time series data using linear spatial/angular kinematics traditionally makes quantification of human movement using low-cost cameras such as the Kinect sensor. Through this conventional approach, interactions between body joints are difficult to analyze and coordination parameters remain hidden. Dynamic Systems Theory (DST) provides a non-linear framework to analyze human movement by representing intersegmental interactions in angle-angle diagrams. DST offers an accurate solution to study coordination in human movement, but it also requires expensive hardware and very specialized biomechanical software. The paper describes a methodological procedure to carry out DST analysis with motion data recorded from the Kinect sensor. Specifically, we address the issue to create and interpret angle-angle diagrams with an emphasis on exploring coordination patterns in motion capture (MoCap) signals. We introduced a method to facilitate the DST analysis and we applied it with two different use cases of human movement analysis in real scenarios: sports gesture study and motion analysis in physical rehabilitation interventions. Results showed that important coordination parameters could be deduced from the angle-angle diagrams improving the understanding of motion data when two joints have to be considered. Therefore, we demonstrated that DST analysis could be performed with inexpensive tools providing a promissory approach for coordination and motor synchronization analysis in novel serious games for health.
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