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

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

doi:10.1114/1.69

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 journal › Article › peer-review

6 Scopus citations

Abstract

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 language	English (US)
Pages (from-to)	859-869
Number of pages	11
Journal	Annals of biomedical engineering
Volume	26
Issue number	5
DOIs	https://doi.org/10.1114/1.69
State	Published - 1998
Externally published	Yes

Keywords

Electrogastrography
Evolutionary programming
Gastric motility
Matching pursuit
Spectral analysis
Stomach

ASJC Scopus subject areas

Biomedical Engineering

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10.1114/1.69

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@article{d175a9bda6384a12ad1a910c55054b3c,

title = "Optimized overcomplete signal representation and its applications to time-frequency analysis of electrogastrogram",

abstract = "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.",

keywords = "Electrogastrography, Evolutionary programming, Gastric motility, Matching pursuit, Spectral analysis, Stomach",

author = "Zhishun Wang and Zhenya He and Chen, {J. D.Z.}",

note = "Funding Information: This work was supported by the climbing program-national key project for fundamental research in China Grant No. NSC92093 and a biomedical engineering research grant from the Whitaker Foundation. The authors would also like to express their gratitude to Loretta Dun-naway for her assistance in the preparation of the manuscript.",

year = "1998",

doi = "10.1114/1.69",

language = "English (US)",

volume = "26",

pages = "859--869",

journal = "Annals of biomedical engineering",

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TY - JOUR

T1 - Optimized overcomplete signal representation and its applications to time-frequency analysis of electrogastrogram

AU - Wang, Zhishun

AU - He, Zhenya

AU - Chen, J. D.Z.

N1 - Funding Information: This work was supported by the climbing program-national key project for fundamental research in China Grant No. NSC92093 and a biomedical engineering research grant from the Whitaker Foundation. The authors would also like to express their gratitude to Loretta Dun-naway for her assistance in the preparation of the manuscript.

PY - 1998

Y1 - 1998

N2 - 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.

AB - 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.

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KW - Evolutionary programming

KW - Gastric motility

KW - Matching pursuit

KW - Spectral analysis

KW - Stomach

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

Abstract

Keywords

ASJC Scopus subject areas

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