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Adaptive neuro-fuzzy inference systems for extracting fetal electrocardiogram

  • American University of Sharjah

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

20 Scopus citations

Abstract

In this paper, we present an efficient technique for extracting the fetal electrocardiogram (FECG) from a composite ECG recording. Our technique uses an adaptive neuro-fuzzy inference system (ANFIS) that operates on two ECG signals recorded at the thoracic and abdominal areas of the mother's skin. The thoracic ECG is assumed to be purely maternal. However, the abdominal ECG will contain both a maternal component as well as a fetal one. This maternal component is considered to be a nonlinearly transformed version of the thoracic ECG. Once this nonlinear transformation is determined, the thoracic ECG signal can be aligned with the maternal component in the abdominal ECG signal. We use ANFIS to perform this nonlinear alignment. The FECG signal is then extracted by simply subtracting the aligned version of the thoracic ECG signal from the abdominal ECG signal.

Original languageEnglish
Title of host publicationSixth IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2006
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages122-126
Number of pages5
ISBN (Print)0780397541, 9780780397545
DOIs
StatePublished - 2006
Externally publishedYes
Event6th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2006 - Vancouver, BC, Canada
Duration: 27 Aug 200630 Aug 2006

Publication series

NameSixth IEEE International Symposium on Signal Processing and Information Technology, ISSPIT

Conference

Conference6th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2006
Country/TerritoryCanada
CityVancouver, BC
Period27/08/0630/08/06

Keywords

  • Adaptive neuron-fuzzy systems
  • Fetal electrocardiogram
  • Noninvasive extraction
  • Nonlinear transformation

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