Optimized overcomplete signal representation and its applications to time-frequency analysis of electrogastrogram

Zhishun Wang, Zhenya He, J. D.Z. Chen

Research output: Contribution to journalArticlepeer-review


The electrogastrogram (EGG) is a surface measurement of gastric myoelectrical activity. The normal frequency of gastric myoelectrical activity in humans is 3 cycles/min. Abnormal frequencies in gastric myoelectrical activity have been found to be associated with functional disorders of the stomach. The aim of this article was, therefore, to develop new timefrequency analysis methods for the detection of gastric dysrhythmia from the EGG. A concept of overcomplete signal representation was used. Two algorithms were proposed for the optimization of the overcomplete signal representation. One was a fast algorithm of matching pursuit and the other was based on an evolutionary program. Computer simulations were performed to compare the performance of the proposed methods in comparison with existing time-frequency analysis methods. It was found that the proposed algorithms provide higher frequency resolution than the short time Fourier transform and Wigner-Ville distribution methods. The practical application of the developed methods to the EGG is also presented. It was concluded that these methods are well suited for the timefrequency analysis of the EGG and may also be applicable to the time-frequency analysis of other biomedical signals.

Original languageEnglish (US)
Pages (from-to)859-869
Number of pages11
JournalAnnals of biomedical engineering
Issue number5
StatePublished - 1998
Externally publishedYes


  • Electrogastrography
  • Evolutionary programming
  • Gastric motility
  • Matching pursuit
  • Spectral analysis
  • Stomach

ASJC Scopus subject areas

  • Biomedical Engineering


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