APPLICATION OF CONTINUOUS WAVELET TRANSFORM IN THE ANALYSIS OF ELECTROCARDIOGRAM SIGNALS

A. Al Maamari, E. Balakrishnan*, S. Narasimman

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The electrocardiogram is known as a primary and powerful diagnostic tool that provides all essential information about the health of our heart. The feature extraction of electrocardiogram, such as R-peak detection, is the central core of any electrocardiogram analysis. Study of electrocardiogram in wavelet domain using continuous wavelet transform with well-known wavelets and other proposed wavelets for this investigation is found to be helpful and yields reasonably reliable results. In order to validate this method, we apply it to several MIT-BIH database records. The continuous wavelet transform with one of the proposed wavelets namely, Mxr-1, achieves 99.97 % sensitivity, 99.89 % positive predictivity, and 0.135 % detection error for accurate detection of R peaks in comparison with the well-known standard wavelets such as Morlet, Mexican hat and Daubechies 4 and two other proposed mother wavelets Mxr-2 and Mxr-3

Original languageEnglish
Pages (from-to)103-118
Number of pages16
JournalInternational Journal of Applied Mathematics
Volume35
Issue number1
DOIs
Publication statusPublished - 2022

Keywords

  • Continuous wavelet transform
  • Daubechies 4
  • Electrocardiogram
  • Mexican hat
  • Morlet
  • R-peaks

ASJC Scopus subject areas

  • Mathematics(all)
  • Computational Theory and Mathematics

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