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Signal detection based on atrial fibrillation detection algorithms using RR interval measurements

Atrial Fibrillation (AF) is the most well-known type of heart disease, which can lead to consequences such as stroke, heart failure, and other health issues. Current methods involve performing large-area ablation without knowing the exact location of key parts. The technology's dependability ca...

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Main Authors: Kong, Pang Seng, Ahmad, Nasarudin, Hassan, Fazilah, Abdul Manaf, Mohamad Shukri, Wahid, Herman, Ahmad, Anita
Format: Conference or Workshop Item
Published: 2022
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/98806/
http://dx.doi.org/10.1007/978-981-19-3923-5_51
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spelling my.utm.988062023-02-02T09:10:57Z http://eprints.utm.my/id/eprint/98806/ Signal detection based on atrial fibrillation detection algorithms using RR interval measurements Kong, Pang Seng Ahmad, Nasarudin Hassan, Fazilah Abdul Manaf, Mohamad Shukri Wahid, Herman Ahmad, Anita TK Electrical engineering. Electronics Nuclear engineering Atrial Fibrillation (AF) is the most well-known type of heart disease, which can lead to consequences such as stroke, heart failure, and other health issues. Current methods involve performing large-area ablation without knowing the exact location of key parts. The technology's dependability can be used as a target for catheter ablation of atrial fibrillation. The goal of the study is to provide a method for detecting AF that may be utilised in medical practice as a screening tool. The essential objectives for the discovery strategy's configuration are to develop a MATLAB software program that can analyze the complexity of an ordinary ECG signal and an AF ECG signal. The Discrete Wavelet Transform (DWT) is utilized to preprocess the ECG signal. The R peaks and RR Interval of the ECG signal can currently accomplish this. In this study, detection of AF is based on the RR Interval Measurements which are coefficient of variance (CV) and normalised root mean square successive difference (nRMSSD). The threshold value for both RR Interval Measurements for detecting an AF signal is 0.1. As a result, 56.52% of the MIT-BIH Atrial Fibrillation Database and 31.81% of MIT-BIH Arrhythmia Database are identified as AF signals because these signals reach the threshold. 2022 Conference or Workshop Item PeerReviewed Kong, Pang Seng and Ahmad, Nasarudin and Hassan, Fazilah and Abdul Manaf, Mohamad Shukri and Wahid, Herman and Ahmad, Anita (2022) Signal detection based on atrial fibrillation detection algorithms using RR interval measurements. In: 3rd International Conference on Control, Instrumentation and Mechatronics Engineering, CIM 2022, 2 March 2022 - 3 March 2022, Virtual, Online. http://dx.doi.org/10.1007/978-981-19-3923-5_51
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/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Kong, Pang Seng
Ahmad, Nasarudin
Hassan, Fazilah
Abdul Manaf, Mohamad Shukri
Wahid, Herman
Ahmad, Anita
Signal detection based on atrial fibrillation detection algorithms using RR interval measurements
description Atrial Fibrillation (AF) is the most well-known type of heart disease, which can lead to consequences such as stroke, heart failure, and other health issues. Current methods involve performing large-area ablation without knowing the exact location of key parts. The technology's dependability can be used as a target for catheter ablation of atrial fibrillation. The goal of the study is to provide a method for detecting AF that may be utilised in medical practice as a screening tool. The essential objectives for the discovery strategy's configuration are to develop a MATLAB software program that can analyze the complexity of an ordinary ECG signal and an AF ECG signal. The Discrete Wavelet Transform (DWT) is utilized to preprocess the ECG signal. The R peaks and RR Interval of the ECG signal can currently accomplish this. In this study, detection of AF is based on the RR Interval Measurements which are coefficient of variance (CV) and normalised root mean square successive difference (nRMSSD). The threshold value for both RR Interval Measurements for detecting an AF signal is 0.1. As a result, 56.52% of the MIT-BIH Atrial Fibrillation Database and 31.81% of MIT-BIH Arrhythmia Database are identified as AF signals because these signals reach the threshold.
format Conference or Workshop Item
author Kong, Pang Seng
Ahmad, Nasarudin
Hassan, Fazilah
Abdul Manaf, Mohamad Shukri
Wahid, Herman
Ahmad, Anita
author_facet Kong, Pang Seng
Ahmad, Nasarudin
Hassan, Fazilah
Abdul Manaf, Mohamad Shukri
Wahid, Herman
Ahmad, Anita
author_sort Kong, Pang Seng
title Signal detection based on atrial fibrillation detection algorithms using RR interval measurements
title_short Signal detection based on atrial fibrillation detection algorithms using RR interval measurements
title_full Signal detection based on atrial fibrillation detection algorithms using RR interval measurements
title_fullStr Signal detection based on atrial fibrillation detection algorithms using RR interval measurements
title_full_unstemmed Signal detection based on atrial fibrillation detection algorithms using RR interval measurements
title_sort signal detection based on atrial fibrillation detection algorithms using rr interval measurements
publishDate 2022
url http://eprints.utm.my/id/eprint/98806/
http://dx.doi.org/10.1007/978-981-19-3923-5_51
_version_ 1758578022178357248
score 13.211869

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