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The wavelet transform as a tool for recognition of biosignals

T A Gyaw1, S R Ray

  • 1Department of Computer Science, University of Illinois at Urbana-Champaign 61801.

Biomedical Sciences Instrumentation
|January 1, 1994
PubMed
Summary

Zero-crossings of wavelet transforms offer a translation-invariant method for signal analysis. This technique enables effective recognition of biosignal patterns within complex data streams, advancing signal processing applications.

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Area of Science:

  • Signal Processing
  • Biomedical Engineering
  • Pattern Recognition

Background:

  • Wavelet transform is a powerful signal analysis tool.
  • Signal variation points are key for information extraction.
  • Direct wavelet transform application in pattern recognition is hindered by translation variance.

Purpose of the Study:

  • To explore the use of zero-crossings in wavelet transforms for pattern recognition.
  • To demonstrate the recognition of biosignal segments within signal streams.
  • To investigate the feasibility of using zero-crossings for searching biosignal libraries.

Main Methods:

  • Utilizing zero-crossings of a specific wavelet transform class.
  • Employing a representation based on zero-crossings and inter-crossing structure.
  • Applying this representation to identify biosignal segments.

Main Results:

  • Zero-crossings provide translation-invariant locations of signal variations.
  • The proposed representation enables recognition of embedded biosignal segments.
  • The method shows feasibility for pattern searching in biosignal databases.

Conclusions:

  • Zero-crossings of wavelet transforms are a viable tool for pattern recognition in biosignals.
  • This approach overcomes the translation variance issue of standard wavelet transforms.
  • The method facilitates efficient searching and identification of specific biosignal patterns.

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