Morphological processing of physiological signals for feature extraction

Research output: Contribution to book or proceedingConference articlepeer-review

3 Scopus citations

Abstract

The paper proposes a novel method of extracting features from physiological signals using intrinsic mode decomposition (IMD) and morphological signal processing (MSP). The complex, nonlinear and non-stationary biomedical signals are first decomposed into intrinsic mode functions (IMF). Next each IMF is subjected to MSP for extracting features, namely, pattern spectrum entropy, that characterize the shape-size complexity of the component signals. These along with other features like energy and sample entropy are extracted from the individual IMF as well as the cumulative sums of IMF for characterizing the signals. The procedure is illustrated using heart sound signals digitally recorded during cardiac auscultation representing different cardiac conditions.

Original languageEnglish
Title of host publicationProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationEngineering the Future of Biomedicine, EMBC 2009
PublisherIEEE Computer Society
Pages324-327
Number of pages4
ISBN (Print)9781424432967
DOIs
StatePublished - 2009
EventAnnual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine - Minneapolis, United States
Duration: Sep 2 2009Sep 6 2009
Conference number: 31
https://ieeexplore.ieee.org/servlet/opac?punumber=5307844

Publication series

NameProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009

Conference

ConferenceAnnual International Conference of the IEEE Engineering in Medicine and Biology Society
Abbreviated titleIEEE EMBC
Country/TerritoryUnited States
CityMinneapolis
Period09/2/0909/6/09
Internet address

Scopus Subject Areas

  • Cell Biology
  • Developmental Biology
  • Biomedical Engineering
  • General Medicine

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