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Wavelets—a new tool in sleep biosignal analysis
Author(s) -
JOBERT MARC,
TISMER CHRISTIAN,
POISEAU ERIC,
SCHULZ HARTMUT
Publication year - 1994
Publication title -
journal of sleep research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.297
H-Index - 117
eISSN - 1365-2869
pISSN - 0962-1105
DOI - 10.1111/j.1365-2869.1994.tb00135.x
Subject(s) - biosignal , wavelet , computer science , wavelet transform , harmonic wavelet transform , discrete wavelet transform , pattern recognition (psychology) , signal processing , gabor wavelet , artificial intelligence , speech recognition , second generation wavelet transform , constant q transform , stationary wavelet transform , computer vision , digital signal processing , filter (signal processing) , computer hardware
SUMMARY The wavelet transform is a relatively new approach to data processing which has been applied in different areas such as signal, speech and image processing. In the last decade, many papers have been published on wavelet theory and its applications. The wavelet transform provides an elegant alternative to the classical Fourier or Gabor transforms unifying numerous signal processing techniques in a common framework. The purpose of the present paper is to provide an overview of the applicability of the wavelet transform to EEG signal analysis. In the first part of the paper the mathematical background is summarized. In the second part, applications to the sleep EEG field are presented and discussed. The results of these illustrations demonstrate the usefulness of the wavelet transform to solve various problems including signal parametrization, pattern recognition and biosignal representation.