Development of analytical approach for an automated analysis of continuous long-term single lead ECG for diagnosis of paroxysmal atrioventricular block

Muammar M. Kabir, Larisa G. Tereshchenko

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Reliable detection of significant ECG features such as the P-wave, QRS-complex and T-wave are of major clinical importance, In this paper we introduce a new algorithm based on synchrosqueezing wavelet transform for detection of P-waves in long-term ECG recordings. Synchrosqueezing is a powerful time-frequency analysis tool that provides precise frequency representation of a multicomponent signal through mode decomposition. First, we analyzed four wavelet filters with different filter parameters, to identifY the best specification for quantification of QRS and P-wave. Second, the algorithm was tested on ECG recording comprising of events with paroxysmal atrioventricular block and validated through visual scanning. Using morlet wavelet with a peak frequency of 5Hz and separation of 0.1 Hz, our proposed algorithm was able to detect 95.5% of P-waves. From this study, it appears that synchrosqueezing wavelet transform may provide a powerful robust technique for automated ECG analysis.

Original languageEnglish (US)
Title of host publicationComputing in Cardiology
PublisherIEEE Computer Society
Pages913-916
Number of pages4
Volume41
EditionJanuary
StatePublished - 2014
Externally publishedYes
Event41st Computing in Cardiology Conference, CinC 2014 - Cambridge, United States
Duration: Sep 7 2014Sep 10 2014

Other

Other41st Computing in Cardiology Conference, CinC 2014
CountryUnited States
CityCambridge
Period9/7/149/10/14

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine
  • Computer Science(all)

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