Classification of paroxysmal atrial fibrillation using second order system

In this paper, we monitored and analyzed the characteristics of atrial fibrillation in patient using second order approach. Atrial fibrillation is a type of atria arrhythmias, disturbing the normal heart rhythm between the atria and lower ventricles of the heart. Heart disease and hypertension incre...

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Main Authors: Abdul Kadir, Nurul Ashikin, Mat Safri, Norlaili, Othman, Mohd. Afzan
Format: Article
Language:English
Published: Penerbit UTM 2014
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Online Access:http://eprints.utm.my/id/eprint/52123/1/NurulAshikinAbdul2014_Classificationofparoxysmalatrial.pdf
http://eprints.utm.my/id/eprint/52123/
http://dx.doi.org/10.11113/jt.v67.2765
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spelling my.utm.521232018-09-17T03:47:15Z http://eprints.utm.my/id/eprint/52123/ Classification of paroxysmal atrial fibrillation using second order system Abdul Kadir, Nurul Ashikin Mat Safri, Norlaili Othman, Mohd. Afzan TK Electrical engineering. Electronics Nuclear engineering In this paper, we monitored and analyzed the characteristics of atrial fibrillation in patient using second order approach. Atrial fibrillation is a type of atria arrhythmias, disturbing the normal heart rhythm between the atria and lower ventricles of the heart. Heart disease and hypertension increase risk of stroke from atrial fibrillation. This study used electrocardiogram (ECG) signals from Physiobank, namely MIT-BIH Atrial Fibrillation Dataset and MIT-BIH Normal Sinus Rhythm Dataset. In total, 865 episodes for each type of ECG signal were classified, specifically normal sinus rhythm (NSR) of human without arrhythmia, normal sinus rhythm of atrial fibrillation patient (N) and atrial fibrillation (AF). Extracted parameters (forcing input, natural frequency and damping coefficient) from second order system were characterized and analyzed. Their ratios, time derivatives, and differential derivatives were also observed. Altogether, 12 parameters were extracted and analysed from the approach. The results show significant difference between the three ECGs of forcing input, and derivative of forcing input. Overall system performance gives specificity and sensitivity of 84.9 % and 85.5 %, respectively Penerbit UTM 2014 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/52123/1/NurulAshikinAbdul2014_Classificationofparoxysmalatrial.pdf Abdul Kadir, Nurul Ashikin and Mat Safri, Norlaili and Othman, Mohd. Afzan (2014) Classification of paroxysmal atrial fibrillation using second order system. Jurnal Teknologi (Sciences and Engineering), 67 (3). pp. 57-64. ISSN 2180-3722 http://dx.doi.org/10.11113/jt.v67.2765 DOI: 10.11113/jt.v67.2765
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Abdul Kadir, Nurul Ashikin
Mat Safri, Norlaili
Othman, Mohd. Afzan
Classification of paroxysmal atrial fibrillation using second order system
description In this paper, we monitored and analyzed the characteristics of atrial fibrillation in patient using second order approach. Atrial fibrillation is a type of atria arrhythmias, disturbing the normal heart rhythm between the atria and lower ventricles of the heart. Heart disease and hypertension increase risk of stroke from atrial fibrillation. This study used electrocardiogram (ECG) signals from Physiobank, namely MIT-BIH Atrial Fibrillation Dataset and MIT-BIH Normal Sinus Rhythm Dataset. In total, 865 episodes for each type of ECG signal were classified, specifically normal sinus rhythm (NSR) of human without arrhythmia, normal sinus rhythm of atrial fibrillation patient (N) and atrial fibrillation (AF). Extracted parameters (forcing input, natural frequency and damping coefficient) from second order system were characterized and analyzed. Their ratios, time derivatives, and differential derivatives were also observed. Altogether, 12 parameters were extracted and analysed from the approach. The results show significant difference between the three ECGs of forcing input, and derivative of forcing input. Overall system performance gives specificity and sensitivity of 84.9 % and 85.5 %, respectively
format Article
author Abdul Kadir, Nurul Ashikin
Mat Safri, Norlaili
Othman, Mohd. Afzan
author_facet Abdul Kadir, Nurul Ashikin
Mat Safri, Norlaili
Othman, Mohd. Afzan
author_sort Abdul Kadir, Nurul Ashikin
title Classification of paroxysmal atrial fibrillation using second order system
title_short Classification of paroxysmal atrial fibrillation using second order system
title_full Classification of paroxysmal atrial fibrillation using second order system
title_fullStr Classification of paroxysmal atrial fibrillation using second order system
title_full_unstemmed Classification of paroxysmal atrial fibrillation using second order system
title_sort classification of paroxysmal atrial fibrillation using second order system
publisher Penerbit UTM
publishDate 2014
url http://eprints.utm.my/id/eprint/52123/1/NurulAshikinAbdul2014_Classificationofparoxysmalatrial.pdf
http://eprints.utm.my/id/eprint/52123/
http://dx.doi.org/10.11113/jt.v67.2765
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score 13.214268