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A Surrogate Technique for Investigating Deterministic Dynamics in Discrete Human Movement

机译:研究离散人体运动中确定性动力学的替代技术

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摘要

Entropy is an effective tool for investigation of human movement variability. However, before applying entropy, it can be beneficial to employ analyses to confirm that observed data are not solely the result of stochastic processes. This can be achieved by contrasting observed data with that produced using surrogate methods. Unlike continuous movement, no appropriate method has been applied to discrete human movement. This article proposes a novel surrogate method for discrete movement data, outlining the processes for determining its critical values. The proposed technique reliably generated surrogates for discrete joint angle time series, destroying fine-scale dynamics of the observed signal, while maintaining macro structural characteristics. Comparison of entropy estimates indicated observed signals had greater regularity than surrogates and were not only the result of stochastic but also deterministic processes. The proposed surrogate method is both a valid and reliable technique to investigate determinism in other discrete human movement time series.
机译:熵是研究人体运动变异性的有效工具。但是,在应用熵之前,使用分析来确认观察到的数据不仅是随机过程的结果可能是有益的。这可以通过将观察到的数据与使用替代方法产生的数据进行对比来实现。与连续运动不同,没有适当的方法应用于离散的人类运动。本文提出了一种用于离散运动数据的新颖替代方法,概述了确定其临界值的过程。所提出的技术可靠地生成了离散关节角时间序列的替代物,破坏了观测信号的精细尺度动力学,同时保持了宏观结构特征。熵估计值的比较表明,观察到的信号比替代信号具有更大的规律性,不仅是随机的,而且是确定性过程的结果。所提出的替代方法是研究其他离散人类运动时间序列中确定性的有效且可靠的技术。

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