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Time-Frequency Analysis of Clinical Percussion Signals Using Matrix Pencil Method

机译：矩阵笔法对临床敲击信号进行时频分析

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摘要

This paper discusses time-frequency analysis of clinical percussion signals produced by tapping over human chest or abdomen with a neurological hammer and recorded with an air microphone. The analysis of short, highly damped percussion signals using conventional time-frequency distributions (TFDs) meets certain difficulties, such as poor time-frequency localization, cross terms, and masking of the lower energy features by the higher energy ones. The above shortcomings lead to inaccurate and ambiguous representation of the signal behavior in the time-frequency plane. This work describes an attempt to construct a TF representation specifically tailored to clinical percussion signals to achieve better resolution of individual components corresponding to physical oscillation modes. Matrix Pencil Method (MPM) is used to decompose the signal into a set of exponentially damped sinusoids, which are then plotted in the time-frequency plane. Such representation provides better visualization of the signal structure than the commonly used frequency-amplitude plots and facilitates tracking subtle changes in the signal for diagnostic purposes. The performance of our approach has been verified on both ideal and real percussion signals. The MPM-based time-frequency analysis appears to be a better choice for clinical percussion signals than conventional TFDs, while its ability to visualize damping has immediate practical applications.
机译：本文讨论了用神经锤敲击人的胸部或腹部并用空气麦克风记录的临床敲击信号的时频分析。使用常规时频分布（TFD）来分析短而高阻尼的打击乐器信号会遇到某些困难，例如时频局部性差，交叉项以及用高能特征掩盖低能特征。上述缺点导致在时频平面中信号行为的表示不准确和模棱两可。这项工作描述了尝试构建专门针对临床打击信号的TF表示，以实现与物理振荡模式相对应的单个组件的更好分辨率的尝试。矩阵笔法（MPM）用于将信号分解为一组指数衰减的正弦波，然后将其绘制在时频平面中。与常用的频率-幅度图相比，这种表示提供了更好的信号结构可视化，并有助于跟踪信号中的细微变化以用于诊断目的。我们的方法的性能已在理想和真实打击乐器信号上得到验证。与常规的TFD相比，基于MPM的时频分析似乎是临床敲击信号的更好选择，而其可视化阻尼的能力已立即得到实际应用。

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  • 来源
    《Journal of electrical and computer engineering》 |2015年第2015期|274541.1-274541.10|共10页
  • 作者

    Moinuddin Bhuiyan; Eugene V. Malyarenko; Mircea A. Pantea; Dante Capaldi; Alfred E. Baylor; Roman Gr. Maev;

  • 作者单位

    Department of Physics, University of Windsor, 401 Sunset Avenue, Windsor, ON, Canada N9B 3P4;

    Tessonics Corp., 2019 Hazel Street, Birmingham, MI 48009, USA;

    Institute for Diagnostic Imaging Research, University of Windsor, 401 Sunset Avenue, Windsor, ON, Canada N9B 3P4;

    Institute for Diagnostic Imaging Research, University of Windsor, 401 Sunset Avenue, Windsor, ON, Canada N9B 3P4;

    Detroit Medical Center, 4201 St. Antoine Street, Detroit, MI 48201, USA;

    Department of Physics, University of Windsor, 401 Sunset Avenue, Windsor, ON, Canada N9B 3P4,Tessonics Corp., 2019 Hazel Street, Birmingham, MI 48009, USA,Institute for Diagnostic Imaging Research, University of Windsor, 401 Sunset Avenue, Windsor, ON, Canada N9B 3P4;

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