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Bicepstral deconvolution of the surface electromyogram.

机译:表面肌电图的二峰倒卷积。

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摘要

A new method of analyzing the surface electromyogram (SEMG) has been developed, in which each SEMG is characterized by a single "representative surface motor unit action potential" (RSMUAP). This method is based upon modelling the SEMG as the output of a linear time-invariant system that has an impulse response equal to the RSMUAP. The RSMUAP can then be recovered from the SEMG using a technique called bicepstral deconvolution. Bicepstral deconvolution is a homomorphic method of separating signals that is based upon the bispectrum. Using the bispectrum, rather than the power spectrum is required for a non-minimum phase estimation of the RSMUAP. The bispectrum has the added benefit of being zero for Gaussian signals, making it well suited for analyzing noisy data. Simulations indicate that this new method of SEMG analysis should be effective for detecting the progression of myopathy.
机译:已经开发了一种分析表面肌电图(SEMG)的新方法,其中每个SEMG都具有一个“代表表面电机单位动作电位”(RSMUAP)。该方法基于将SEMG建模为线性时不变系统的输出,该系统的脉冲响应等于RSMUAP。然后可以使用称为二头肌消除卷积的技术从SEMG中恢复RSMUAP。双频谱去卷积是一种基于双谱分离信号的同态方法。对于RSMUAP的非最小相位估计,需要使用双频谱而不是功率谱。对于高斯信号,双谱具有附加优势,即为零,使其非常适合分析噪声数据。仿真表明,这种新的SEMG分析方法应可有效检测肌病的进展。

著录项

  • 作者

    Does, Mark Douglas.;

  • 作者单位

    University of Alberta (Canada).;

  • 授予单位 University of Alberta (Canada).;
  • 学科 Engineering Biomedical.;Engineering Electronics and Electrical.
  • 学位 M.Sc.
  • 年度 1993
  • 页码 102 p.
  • 总页数 102
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 老年病学;
  • 关键词

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