Computer-aided diagnosis of atrial fibrillation based on ECG Signals: A review

Abstract 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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