Computer-aided diagnosis of atrial fibrillation based on ECG Signals: A review
•Existing AF detection techniques are discussed.•Building blocks of CADx system are described.•Different features explored by researchers are presented.•State-of-art CADx system for AF are highlighted. Arrhythmia is a type of disorder that affects the pattern and rate of the heartbeat. Among the var...
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| Published in | Information sciences Vol. 467; pp. 99 - 114 |
|---|---|
| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Inc
01.10.2018
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0020-0255 1872-6291 |
| DOI | 10.1016/j.ins.2018.07.063 |
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| Abstract | •Existing AF detection techniques are discussed.•Building blocks of CADx system are described.•Different features explored by researchers are presented.•State-of-art CADx system for AF are highlighted.
Arrhythmia is a type of disorder that affects the pattern and rate of the heartbeat. Among the various arrhythmia conditions, atrial fibrillation (AF) is the most prevalent. AF is associated with a chaotic, and frequently fast, heartbeat. Moreover, AF increases the risk of cardioembolic stroke and other heart-related problems such as heart failure. Thus, it is necessary to screen for AF and receive proper treatment before the condition progresses. To date, electrocardiogram (ECG) feature analysis is the gold standard for the diagnosis of AF. However, because it is time-varying, AF ECG signals are difficult to interpret. The ECG signals are often contaminated with noise. Further, manual interpretation of ECG signals may be subjective, time-consuming, and susceptible to inter-observer variabilities. Various computer-aided diagnosis (CADx) methods have been proposed to remedy these shortcomings. In this paper, different CADx systems developed by researchers are discussed. Also, the potentials of the CADx system are highlighted.
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| AbstractList | •Existing AF detection techniques are discussed.•Building blocks of CADx system are described.•Different features explored by researchers are presented.•State-of-art CADx system for AF are highlighted.
Arrhythmia is a type of disorder that affects the pattern and rate of the heartbeat. Among the various arrhythmia conditions, atrial fibrillation (AF) is the most prevalent. AF is associated with a chaotic, and frequently fast, heartbeat. Moreover, AF increases the risk of cardioembolic stroke and other heart-related problems such as heart failure. Thus, it is necessary to screen for AF and receive proper treatment before the condition progresses. To date, electrocardiogram (ECG) feature analysis is the gold standard for the diagnosis of AF. However, because it is time-varying, AF ECG signals are difficult to interpret. The ECG signals are often contaminated with noise. Further, manual interpretation of ECG signals may be subjective, time-consuming, and susceptible to inter-observer variabilities. Various computer-aided diagnosis (CADx) methods have been proposed to remedy these shortcomings. In this paper, different CADx systems developed by researchers are discussed. Also, the potentials of the CADx system are highlighted.
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| Author | Hagiwara, Yuki Oh, Shu Lih Tan, Jen Hong Fujita, Hamido Tan, Ru San Ciaccio, Edward J Acharya, U Rajendra |
| Author_xml | – sequence: 1 givenname: Yuki surname: Hagiwara fullname: Hagiwara, Yuki organization: Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore – sequence: 2 givenname: Hamido orcidid: 0000-0001-5256-210X surname: Fujita fullname: Fujita, Hamido email: hfujita-799@acm.org organization: Iwate Prefectural University, Faculty of Software and Information Science, Iwate, Japan – sequence: 3 givenname: Shu Lih surname: Oh fullname: Oh, Shu Lih organization: Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore – sequence: 4 givenname: Jen Hong surname: Tan fullname: Tan, Jen Hong organization: National University of Singapore, Institute of System Science, Singapore – sequence: 5 givenname: Ru San surname: Tan fullname: Tan, Ru San organization: Department of Cardiology, National Heart Centre Singapore, Singapore – sequence: 6 givenname: Edward J surname: Ciaccio fullname: Ciaccio, Edward J organization: Department of Medicine - Division of Cardiology, Columbia University College of Physicians and Surgeons, New York, USA – sequence: 7 givenname: U Rajendra surname: Acharya fullname: Acharya, U Rajendra organization: Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore |
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| Keywords | Computer-aided diagnosis system Electrocardiogram signals Arrhythmia Atrial fibrillation Machine learning |
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| Score | 2.593566 |
| Snippet | •Existing AF detection techniques are discussed.•Building blocks of CADx system are described.•Different features explored by researchers are... |
| SourceID | crossref elsevier |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 99 |
| SubjectTerms | Arrhythmia Atrial fibrillation Computer-aided diagnosis system Electrocardiogram signals Machine learning |
| Title | Computer-aided diagnosis of atrial fibrillation based on ECG Signals: A review |
| URI | https://dx.doi.org/10.1016/j.ins.2018.07.063 |
| Volume | 467 |
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