Heart abnormality detection using acceleration plethysmogram signal

For the past decade, irregularities of heart beat, or also known as Cardiac Arrhythmias has led to Cardiovascular Diseases (CVDs). It has been recorded as one of the main death cause in Malaysia as reported by the Ministry of Health Malaysia. This has become a major concern as many patients are unaw...

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Main Authors:	Hussin, Khalida, Sidek, Khairul Azami, Ismail, Ahmad Fadzil
Format:	Article
Language:	English English
Published:	Faculty of Electronic and Computer Engineering (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM) 2018
Subjects:	TK7885 Computer engineering
Online Access:	http://irep.iium.edu.my/63340/ http://irep.iium.edu.my/63340/ http://irep.iium.edu.my/63340/1/3657-9763-1-SM.pdf http://irep.iium.edu.my/63340/7/633340%20Heart%20abnormality%20detection%20using%20acceleration%20plethysmogram%20signal%20SCOPUS.pdf

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recordtype	eprints
spelling	iium-633402018-04-18T01:26:35Z http://irep.iium.edu.my/63340/ Heart abnormality detection using acceleration plethysmogram signal Hussin, Khalida Sidek, Khairul Azami Ismail, Ahmad Fadzil TK7885 Computer engineering For the past decade, irregularities of heart beat, or also known as Cardiac Arrhythmias has led to Cardiovascular Diseases (CVDs). It has been recorded as one of the main death cause in Malaysia as reported by the Ministry of Health Malaysia. This has become a major concern as many patients are unaware that early prevention can save them. In the past years, few systems that detects heart abnormality have been introduced. This includes various types of signal, such as the photoplethysmogram, electrocardiogram, electroencephalo-gram, ballistocardiogram and others. However, each of the systems have their own drawbacks. The study come out with a solution and proposed a system that can aid the problem, which is Heart Abnormality Detection Using Acceleration Plethysmogram (APG) signal. APG is more relevant as it displays obvious segments in the morphological cycle of the waveform. Throughout the study, datasets from PhysioNet, specifically MIMIC II Clinical Database waveform with sampling frequency of 125 Hz were used to obtain PPG and APG waveform. These signals undergoes five main processes before the abnormality can be detected. WEKA software was used for decision making process, where classifiers such as Multi-Layer Perceptron (MLP), Radial Basis Function (RBF) Network, and Bayesian Network were used to differentiate between the normal and abnormal heart beats. The percentage of correctly classified instances produced by the classifiers were able to show the significant differences between normal and abnormal APG signals. Based on the experimentation results, MLP and RBF classifier showed a significantly high classification accuracy of 96% as compared to Bayesian Network of 92%. This outcome suggest that APG signal can be used as an alternative in the detection of heart abnormalities with promising experimentation results. Faculty of Electronic and Computer Engineering (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM) 2018 Article PeerReviewed application/pdf en http://irep.iium.edu.my/63340/1/3657-9763-1-SM.pdf application/pdf en http://irep.iium.edu.my/63340/7/633340%20Heart%20abnormality%20detection%20using%20acceleration%20plethysmogram%20signal%20SCOPUS.pdf Hussin, Khalida and Sidek, Khairul Azami and Ismail, Ahmad Fadzil (2018) Heart abnormality detection using acceleration plethysmogram signal. Journal of Telecommunication, Electronic and Computer Engineering, 10 (1-6). pp. 21-24. ISSN 2180-1843 E-ISSN 2289-8131 http://journal.utem.edu.my/index.php/jtec/index
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TK7885 Computer engineering
spellingShingle	TK7885 Computer engineering Hussin, Khalida Sidek, Khairul Azami Ismail, Ahmad Fadzil Heart abnormality detection using acceleration plethysmogram signal
description	For the past decade, irregularities of heart beat, or also known as Cardiac Arrhythmias has led to Cardiovascular Diseases (CVDs). It has been recorded as one of the main death cause in Malaysia as reported by the Ministry of Health Malaysia. This has become a major concern as many patients are unaware that early prevention can save them. In the past years, few systems that detects heart abnormality have been introduced. This includes various types of signal, such as the photoplethysmogram, electrocardiogram, electroencephalo-gram, ballistocardiogram and others. However, each of the systems have their own drawbacks. The study come out with a solution and proposed a system that can aid the problem, which is Heart Abnormality Detection Using Acceleration Plethysmogram (APG) signal. APG is more relevant as it displays obvious segments in the morphological cycle of the waveform. Throughout the study, datasets from PhysioNet, specifically MIMIC II Clinical Database waveform with sampling frequency of 125 Hz were used to obtain PPG and APG waveform. These signals undergoes five main processes before the abnormality can be detected. WEKA software was used for decision making process, where classifiers such as Multi-Layer Perceptron (MLP), Radial Basis Function (RBF) Network, and Bayesian Network were used to differentiate between the normal and abnormal heart beats. The percentage of correctly classified instances produced by the classifiers were able to show the significant differences between normal and abnormal APG signals. Based on the experimentation results, MLP and RBF classifier showed a significantly high classification accuracy of 96% as compared to Bayesian Network of 92%. This outcome suggest that APG signal can be used as an alternative in the detection of heart abnormalities with promising experimentation results.
format	Article
author	Hussin, Khalida Sidek, Khairul Azami Ismail, Ahmad Fadzil
author_facet	Hussin, Khalida Sidek, Khairul Azami Ismail, Ahmad Fadzil
author_sort	Hussin, Khalida
title	Heart abnormality detection using acceleration plethysmogram signal
title_short	Heart abnormality detection using acceleration plethysmogram signal
title_full	Heart abnormality detection using acceleration plethysmogram signal
title_fullStr	Heart abnormality detection using acceleration plethysmogram signal
title_full_unstemmed	Heart abnormality detection using acceleration plethysmogram signal
title_sort	heart abnormality detection using acceleration plethysmogram signal
publisher	Faculty of Electronic and Computer Engineering (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM)
publishDate	2018
url	http://irep.iium.edu.my/63340/ http://irep.iium.edu.my/63340/ http://irep.iium.edu.my/63340/1/3657-9763-1-SM.pdf http://irep.iium.edu.my/63340/7/633340%20Heart%20abnormality%20detection%20using%20acceleration%20plethysmogram%20signal%20SCOPUS.pdf
first_indexed	2023-09-18T21:29:50Z
last_indexed	2023-09-18T21:29:50Z
_version_	1777412436964409344

Heart abnormality detection using acceleration plethysmogram signal

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