Feature extraction and characterization of cardiovascular arrhythmia and normal sinus rhythm from ECG signals using LabVIEW

Akib Mohammad Azam Zaidi; Muhammad Jubaer Ahmed; A. S.M. Bakibillah

doi:10.1109/ICIVPR.2017.7890871

Feature extraction and characterization of cardiovascular arrhythmia and normal sinus rhythm from ECG signals using LabVIEW

Akib Mohammad Azam Zaidi, Muhammad Jubaer Ahmed, A. S.M. Bakibillah

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other

11 Citations (Scopus)

Abstract

Electrocardiogram (ECG) is a test that represents electrical activity of heart and plays an important role in monitoring the condition of the heart. The diagnosis of cardiac condition is greatly dependent upon ECG signals. This paper presents a method of feature extraction and characterization of ECG signals for normal sinus rhythm and three different types of cardiovascular arrhythmia, namely Slow Term Atrial Fibrillation, Paroxysmal Atrial Fibrillation and Supraventricular Tachycardia. The proposed algorithm is implemented using NI LabVIEW Biomedical Workbench to perform signal processing that extracts features of ECG signal such as heart rate, QRS width, PR interval, QT interval and the RR interval which are then used to characterize both cardiovascular arrhythmia and normal sinus rhythms. About Forty-five sets of data of ECG signals are used in this work for analysis and verification and satisfactory result is obtained.

Original language	English
Title of host publication	2017 IEEE International Conference on Imaging, Vision and Pattern Recognition, icIVPR 2017
Publisher	IEEE, Institute of Electrical and Electronics Engineers
ISBN (Electronic)	9781509060030
DOIs	https://doi.org/10.1109/ICIVPR.2017.7890871
Publication status	Published - 2017
Externally published	Yes
Event	IEEE International Conference on Imaging, Vision and Pattern Recognition 2017 - Dhaka, Bangladesh Duration: 13 Feb 2017 → 13 Feb 2017 https://ieeexplore.ieee.org/xpl/conhome/7886950/proceeding (Proceedings)

Conference

Conference	IEEE International Conference on Imaging, Vision and Pattern Recognition 2017
Abbreviated title	icIVPR 2017
Country/Territory	Bangladesh
City	Dhaka
Period	13/02/17 → 13/02/17
Internet address	https://ieeexplore.ieee.org/xpl/conhome/7886950/proceeding (Proceedings)

Keywords

cardiovascular arrhythmia
Electrodiagram
feature extraction
normal sinus rhythm
signal processing

Access to Document

10.1109/ICIVPR.2017.7890871

Cite this

Zaidi, A. M. A., Ahmed, M. J., & Bakibillah, A. S. M. (2017). Feature extraction and characterization of cardiovascular arrhythmia and normal sinus rhythm from ECG signals using LabVIEW. In 2017 IEEE International Conference on Imaging, Vision and Pattern Recognition, icIVPR 2017 IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICIVPR.2017.7890871

@inproceedings{8adce621a5744eedad13890283f25234,

title = "Feature extraction and characterization of cardiovascular arrhythmia and normal sinus rhythm from ECG signals using LabVIEW",

abstract = "Electrocardiogram (ECG) is a test that represents electrical activity of heart and plays an important role in monitoring the condition of the heart. The diagnosis of cardiac condition is greatly dependent upon ECG signals. This paper presents a method of feature extraction and characterization of ECG signals for normal sinus rhythm and three different types of cardiovascular arrhythmia, namely Slow Term Atrial Fibrillation, Paroxysmal Atrial Fibrillation and Supraventricular Tachycardia. The proposed algorithm is implemented using NI LabVIEW Biomedical Workbench to perform signal processing that extracts features of ECG signal such as heart rate, QRS width, PR interval, QT interval and the RR interval which are then used to characterize both cardiovascular arrhythmia and normal sinus rhythms. About Forty-five sets of data of ECG signals are used in this work for analysis and verification and satisfactory result is obtained.",

keywords = "cardiovascular arrhythmia, Electrodiagram, feature extraction, normal sinus rhythm, signal processing",

author = "Zaidi, {Akib Mohammad Azam} and Ahmed, {Muhammad Jubaer} and Bakibillah, {A. S.M.}",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.; IEEE International Conference on Imaging, Vision and Pattern Recognition 2017, icIVPR 2017 ; Conference date: 13-02-2017 Through 13-02-2017",

year = "2017",

doi = "10.1109/ICIVPR.2017.7890871",

language = "English",

booktitle = "2017 IEEE International Conference on Imaging, Vision and Pattern Recognition, icIVPR 2017",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

url = "https://ieeexplore.ieee.org/xpl/conhome/7886950/proceeding",

}

Zaidi, AMA, Ahmed, MJ & Bakibillah, ASM 2017, Feature extraction and characterization of cardiovascular arrhythmia and normal sinus rhythm from ECG signals using LabVIEW. in 2017 IEEE International Conference on Imaging, Vision and Pattern Recognition, icIVPR 2017. IEEE, Institute of Electrical and Electronics Engineers, IEEE International Conference on Imaging, Vision and Pattern Recognition 2017, Dhaka, Bangladesh, 13/02/17. https://doi.org/10.1109/ICIVPR.2017.7890871

Feature extraction and characterization of cardiovascular arrhythmia and normal sinus rhythm from ECG signals using LabVIEW. / Zaidi, Akib Mohammad Azam; Ahmed, Muhammad Jubaer; Bakibillah, A. S.M.
2017 IEEE International Conference on Imaging, Vision and Pattern Recognition, icIVPR 2017. IEEE, Institute of Electrical and Electronics Engineers, 2017.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other

TY - GEN

T1 - Feature extraction and characterization of cardiovascular arrhythmia and normal sinus rhythm from ECG signals using LabVIEW

AU - Zaidi, Akib Mohammad Azam

AU - Ahmed, Muhammad Jubaer

AU - Bakibillah, A. S.M.

PY - 2017

Y1 - 2017

N2 - Electrocardiogram (ECG) is a test that represents electrical activity of heart and plays an important role in monitoring the condition of the heart. The diagnosis of cardiac condition is greatly dependent upon ECG signals. This paper presents a method of feature extraction and characterization of ECG signals for normal sinus rhythm and three different types of cardiovascular arrhythmia, namely Slow Term Atrial Fibrillation, Paroxysmal Atrial Fibrillation and Supraventricular Tachycardia. The proposed algorithm is implemented using NI LabVIEW Biomedical Workbench to perform signal processing that extracts features of ECG signal such as heart rate, QRS width, PR interval, QT interval and the RR interval which are then used to characterize both cardiovascular arrhythmia and normal sinus rhythms. About Forty-five sets of data of ECG signals are used in this work for analysis and verification and satisfactory result is obtained.

AB - Electrocardiogram (ECG) is a test that represents electrical activity of heart and plays an important role in monitoring the condition of the heart. The diagnosis of cardiac condition is greatly dependent upon ECG signals. This paper presents a method of feature extraction and characterization of ECG signals for normal sinus rhythm and three different types of cardiovascular arrhythmia, namely Slow Term Atrial Fibrillation, Paroxysmal Atrial Fibrillation and Supraventricular Tachycardia. The proposed algorithm is implemented using NI LabVIEW Biomedical Workbench to perform signal processing that extracts features of ECG signal such as heart rate, QRS width, PR interval, QT interval and the RR interval which are then used to characterize both cardiovascular arrhythmia and normal sinus rhythms. About Forty-five sets of data of ECG signals are used in this work for analysis and verification and satisfactory result is obtained.

KW - cardiovascular arrhythmia

KW - Electrodiagram

KW - feature extraction

KW - normal sinus rhythm

KW - signal processing

UR - http://www.scopus.com/inward/record.url?scp=85018179478&partnerID=8YFLogxK

U2 - 10.1109/ICIVPR.2017.7890871

DO - 10.1109/ICIVPR.2017.7890871

M3 - Conference Paper

AN - SCOPUS:85018179478

BT - 2017 IEEE International Conference on Imaging, Vision and Pattern Recognition, icIVPR 2017

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - IEEE International Conference on Imaging, Vision and Pattern Recognition 2017

Y2 - 13 February 2017 through 13 February 2017

ER -

Feature extraction and characterization of cardiovascular arrhythmia and normal sinus rhythm from ECG signals using LabVIEW

Abstract

Conference

Keywords

Access to Document

Other files and links

Cite this