ECG noise reduction with the use of the ant lion optimizer algorithm

The electrocardiogram (ECG) signal is susceptible to noise and artifacts and it is essential to remove that noise in order to support any decision making for automatic heart disorder diagnosis systems. In this paper, the use of Ant Lion Optimizer (ALO) for optimizing and identifying the cutoff frequ...

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Main Authors: Kiew, Hui Hii, Vigneswaran, Narayanamurthy, Fahmi, Samsuri
Format: Article
Language:English
Published: ETASR 2019
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/25845/1/ECG%20noise%20reduction%20with%20the%20use%20of%20the%20ant.pdf
http://umpir.ump.edu.my/id/eprint/25845/
https://www.etasr.com/index.php/ETASR/article/view/2766/pdf
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Institution: Universiti Malaysia Pahang
Language: English
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spelling my.ump.umpir.258452019-11-26T03:23:48Z http://umpir.ump.edu.my/id/eprint/25845/ ECG noise reduction with the use of the ant lion optimizer algorithm Kiew, Hui Hii Vigneswaran, Narayanamurthy Fahmi, Samsuri TK Electrical engineering. Electronics Nuclear engineering The electrocardiogram (ECG) signal is susceptible to noise and artifacts and it is essential to remove that noise in order to support any decision making for automatic heart disorder diagnosis systems. In this paper, the use of Ant Lion Optimizer (ALO) for optimizing and identifying the cutoff frequency of the ECG signal for low-pass filtering is investigated. Generally, the spectrums of the ECG signal are extracted from two classes: arrhythmia and supraventricular. Baseline wander is removed by a moving median filter. A dataset of the extracted features of the ECG spectrums is used to train the ALO. The performance of the ALO is investigated. The ALO-identified cutoff frequency is applied to a Finite Impulse Response (FIR) filter and the resulting signal is evaluated against the original clean and conventional filtered ECG signals. The results show that the intelligent ALO-based system successfully denoised the ECG signals more effectively than the conventional method. The accuracy percentage increased by 2%. ETASR 2019-08 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/25845/1/ECG%20noise%20reduction%20with%20the%20use%20of%20the%20ant.pdf Kiew, Hui Hii and Vigneswaran, Narayanamurthy and Fahmi, Samsuri (2019) ECG noise reduction with the use of the ant lion optimizer algorithm. Engineering, Technology & Applied Science Research, 9 (4). pp. 4525-4529. ISSN 2241-4487 (print); 1792-8036 (online) https://www.etasr.com/index.php/ETASR/article/view/2766/pdf
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Kiew, Hui Hii
Vigneswaran, Narayanamurthy
Fahmi, Samsuri
ECG noise reduction with the use of the ant lion optimizer algorithm
description The electrocardiogram (ECG) signal is susceptible to noise and artifacts and it is essential to remove that noise in order to support any decision making for automatic heart disorder diagnosis systems. In this paper, the use of Ant Lion Optimizer (ALO) for optimizing and identifying the cutoff frequency of the ECG signal for low-pass filtering is investigated. Generally, the spectrums of the ECG signal are extracted from two classes: arrhythmia and supraventricular. Baseline wander is removed by a moving median filter. A dataset of the extracted features of the ECG spectrums is used to train the ALO. The performance of the ALO is investigated. The ALO-identified cutoff frequency is applied to a Finite Impulse Response (FIR) filter and the resulting signal is evaluated against the original clean and conventional filtered ECG signals. The results show that the intelligent ALO-based system successfully denoised the ECG signals more effectively than the conventional method. The accuracy percentage increased by 2%.
format Article
author Kiew, Hui Hii
Vigneswaran, Narayanamurthy
Fahmi, Samsuri
author_facet Kiew, Hui Hii
Vigneswaran, Narayanamurthy
Fahmi, Samsuri
author_sort Kiew, Hui Hii
title ECG noise reduction with the use of the ant lion optimizer algorithm
title_short ECG noise reduction with the use of the ant lion optimizer algorithm
title_full ECG noise reduction with the use of the ant lion optimizer algorithm
title_fullStr ECG noise reduction with the use of the ant lion optimizer algorithm
title_full_unstemmed ECG noise reduction with the use of the ant lion optimizer algorithm
title_sort ecg noise reduction with the use of the ant lion optimizer algorithm
publisher ETASR
publishDate 2019
url http://umpir.ump.edu.my/id/eprint/25845/1/ECG%20noise%20reduction%20with%20the%20use%20of%20the%20ant.pdf
http://umpir.ump.edu.my/id/eprint/25845/
https://www.etasr.com/index.php/ETASR/article/view/2766/pdf
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