小波熵的一种新方法:在姿态信号中的应用

C. Franco, P. Gumery, A. Fleury, N. Vuillerme
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引用次数: 0

摘要

本研究提出了一种新的方法来量化以谱分布为特征的生理信号的复杂性。我们的方法受到小波熵的启发,但基于模态表示:同步压缩变换。对分解影响锥内的每个时间样本进行计算。首先在模拟的多分量信号上对该指标进行了验证和讨论。最后,它被应用于评估姿势控制和使用所有可用感觉资源的能力。结果显示,我们的指数显着差异后诱导变化的感官条件,而传统的方法失败。该指标可能构成一个有前途的工具,以检测姿势的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new approach to wavelet entropy: Application to postural signals
This study proposes a new approach for quantifying complexity of physiological signals characterized by a spectral distribution in modes. Our approach is inspired by wavelet entropy but based on a modal representation: Synchrosqueezing transform. It is calculated for each time sample within the cone of influence of the decomposition. This index is first validated and discussed on simulated multicomponent signals. Finally, it is applied to assess postural control and ability at using all the sensory resources available. Results show significant differences in our index following an induced change in sensory conditions whereas a conventional approach fails. This index may constitute a promising tool for detection of postural troubles.
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