APPLICATION OF CONTINUOUS WAVELET TRANSFORM IN THE ANALYSIS OF ELECTROCARDIOGRAM SIGNALS

A. Al Maamari; E. Balakrishnan; S. Narasimman

doi:10.12732/ijam.v35i1.8

APPLICATION OF CONTINUOUS WAVELET TRANSFORM IN THE ANALYSIS OF ELECTROCARDIOGRAM SIGNALS

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

^*Corresponding author for this work

Mathematics

Research output: Contribution to journal › Article › peer-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

Original language	English
Pages (from-to)	103-118
Number of pages	16
Journal	International Journal of Applied Mathematics
Volume	35
Issue number	1
DOIs	https://doi.org/10.12732/ijam.v35i1.8
Publication status	Published - Mar 23 2022

Keywords

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

ASJC Scopus subject areas

General Mathematics
Computational Theory and Mathematics

Access to Document

10.12732/ijam.v35i1.8

Cite this

@article{4124c07ead4d47d68d6cf12dd2c79e02,

title = "APPLICATION OF CONTINUOUS WAVELET TRANSFORM IN THE ANALYSIS OF ELECTROCARDIOGRAM SIGNALS",

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",

keywords = "Continuous wavelet transform, Daubechies 4, Electrocardiogram, Mexican hat, Morlet, R-peaks",

author = "{Al Maamari}, A. and E. Balakrishnan and S. Narasimman",

note = "Publisher Copyright: {\textcopyright} 2022. Academic Publications",

year = "2022",

month = mar,

day = "23",

doi = "10.12732/ijam.v35i1.8",

language = "English",

volume = "35",

pages = "103--118",

journal = "International Journal of Applied Mathematics",

issn = "1311-1728",

publisher = "Academic Publications Ltd.",

number = "1",

}

TY - JOUR

T1 - APPLICATION OF CONTINUOUS WAVELET TRANSFORM IN THE ANALYSIS OF ELECTROCARDIOGRAM SIGNALS

AU - Al Maamari, A.

AU - Balakrishnan, E.

AU - Narasimman, S.

PY - 2022/3/23

Y1 - 2022/3/23

N2 - 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

AB - 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

KW - Continuous wavelet transform

KW - Daubechies 4

KW - Electrocardiogram

KW - Mexican hat

KW - Morlet

KW - R-peaks

UR - http://www.scopus.com/inward/record.url?scp=85129355260&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85129355260&partnerID=8YFLogxK

U2 - 10.12732/ijam.v35i1.8

DO - 10.12732/ijam.v35i1.8

M3 - Article

AN - SCOPUS:85129355260

SN - 1311-1728

VL - 35

SP - 103

EP - 118

JO - International Journal of Applied Mathematics

JF - International Journal of Applied Mathematics

IS - 1

ER -

APPLICATION OF CONTINUOUS WAVELET TRANSFORM IN THE ANALYSIS OF ELECTROCARDIOGRAM SIGNALS

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this