Continuous wavelet transform and higher-order spectrum: combinatory potentialities in breath sound analysis and electroencephalogram-based pain characterization

Philos Trans A Math Phys Eng Sci. 2018 Aug 13;376(2126):20170249. doi: 10.1098/rsta.2017.0249.

Abstract

The combination of the continuous wavelet transform (CWT) with a higher-order spectrum (HOS) merges two worlds into one that conveys information regarding the non-stationarity, non-Gaussianity and nonlinearity of the systems and/or signals under examination. In the current work, the third-order spectrum (TOS), which is used to detect the nonlinearity and deviation from Gaussianity of two types of biomedical signals, that is, wheezes and electroencephalogram (EEG), is combined with the CWT to offer a time-scale representation of the examined signals. As a result, a CWT/TOS field is formed and a time axis is introduced, creating a time-bifrequency domain, which provides a new means for wheeze nonlinear analysis and dynamic EEG-based pain characterization. A detailed description and examples are provided and discussed to showcase the combinatory potential of CWT/TOS in the field of advanced signal processing.This article is part of the theme issue 'Redundancy rules: the continuous wavelet transform comes of age'.

Keywords: breathsounds; continuous wavelet transform; electroencephalogram; higher-order spectrum; pain characterization; wavelet bispectrum.

MeSH terms

  • Electroencephalography*
  • Humans
  • Pain / diagnosis*
  • Respiratory Sounds / diagnosis*
  • Signal Processing, Computer-Assisted*
  • Wavelet Analysis*