Sleep apnea detection using cardioid based grap

In this study, the development of Cardioid based graph electrocardiogram heart abnormalities classification technique is presented. ECG signals in this work were attained from a public online database UCD Sleep Apnea database (UCDB) with sampling rate of 250 Hz. Each recording has 60 seconds of elec...

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Main Authors:	Mohd Azam, Siti Nurfarah Ain, Sidek, Khairul Azami, Zainal, Nur Izzati
Format:	Article
Language:	English
Published:	Science & Engineering Research Support Society 2016
Subjects:	TK7885 Computer engineering
Online Access:	http://irep.iium.edu.my/52699/ http://irep.iium.edu.my/52699/ http://irep.iium.edu.my/52699/ http://irep.iium.edu.my/52699/1/IJBSBT_Sleep%20Apnea%20Detection%20using%20Cardioid%20Based%20Graph.pdf

id	iium-52699
recordtype	eprints
spelling	iium-526992017-06-02T04:47:48Z http://irep.iium.edu.my/52699/ Sleep apnea detection using cardioid based grap Mohd Azam, Siti Nurfarah Ain Sidek, Khairul Azami Zainal, Nur Izzati TK7885 Computer engineering In this study, the development of Cardioid based graph electrocardiogram heart abnormalities classification technique is presented. ECG signals in this work were attained from a public online database UCD Sleep Apnea database (UCDB) with sampling rate of 250 Hz. Each recording has 60 seconds of electrocardiogram signals. Unique features were extracted using the Pan Tompkins algorithm, later Cardioid based graph was formed as the result of the differentiation process. The various shapes of closed-loop created were then observed. From the Cardioid loop, we evaluated the area and standard deviation to differentiate between normal and abnormal heartbeats. As a result, the area, standard deviation, and mean values of abnormal heartbeat were twice the value of a normal heartbeat thus indicating the differences between two types of heart morphologies. Thus, the output of the study suggests the proof-of-concept of our proposed mechanisms to detect heart abnormalities and has the potential to act as an alternative to the current techniques. Science & Engineering Research Support Society 2016 Article PeerReviewed application/pdf en http://irep.iium.edu.my/52699/1/IJBSBT_Sleep%20Apnea%20Detection%20using%20Cardioid%20Based%20Graph.pdf Mohd Azam, Siti Nurfarah Ain and Sidek, Khairul Azami and Zainal, Nur Izzati (2016) Sleep apnea detection using cardioid based grap. International Journal of Bio-Science and Bio-Technology, 8 (5). pp. 13-22. ISSN 2233-7849 http://www.sersc.org/journals/IJBSBT/vol8_no5/2.pdf 10.14257/ijbsbt.2016.8.5.02
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	TK7885 Computer engineering
spellingShingle	TK7885 Computer engineering Mohd Azam, Siti Nurfarah Ain Sidek, Khairul Azami Zainal, Nur Izzati Sleep apnea detection using cardioid based grap
description	In this study, the development of Cardioid based graph electrocardiogram heart abnormalities classification technique is presented. ECG signals in this work were attained from a public online database UCD Sleep Apnea database (UCDB) with sampling rate of 250 Hz. Each recording has 60 seconds of electrocardiogram signals. Unique features were extracted using the Pan Tompkins algorithm, later Cardioid based graph was formed as the result of the differentiation process. The various shapes of closed-loop created were then observed. From the Cardioid loop, we evaluated the area and standard deviation to differentiate between normal and abnormal heartbeats. As a result, the area, standard deviation, and mean values of abnormal heartbeat were twice the value of a normal heartbeat thus indicating the differences between two types of heart morphologies. Thus, the output of the study suggests the proof-of-concept of our proposed mechanisms to detect heart abnormalities and has the potential to act as an alternative to the current techniques.
format	Article
author	Mohd Azam, Siti Nurfarah Ain Sidek, Khairul Azami Zainal, Nur Izzati
author_facet	Mohd Azam, Siti Nurfarah Ain Sidek, Khairul Azami Zainal, Nur Izzati
author_sort	Mohd Azam, Siti Nurfarah Ain
title	Sleep apnea detection using cardioid based grap
title_short	Sleep apnea detection using cardioid based grap
title_full	Sleep apnea detection using cardioid based grap
title_fullStr	Sleep apnea detection using cardioid based grap
title_full_unstemmed	Sleep apnea detection using cardioid based grap
title_sort	sleep apnea detection using cardioid based grap
publisher	Science & Engineering Research Support Society
publishDate	2016
url	http://irep.iium.edu.my/52699/ http://irep.iium.edu.my/52699/ http://irep.iium.edu.my/52699/ http://irep.iium.edu.my/52699/1/IJBSBT_Sleep%20Apnea%20Detection%20using%20Cardioid%20Based%20Graph.pdf
first_indexed	2023-09-18T21:14:39Z
last_indexed	2023-09-18T21:14:39Z
_version_	1777411480923144192

Sleep apnea detection using cardioid based grap

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