Differentiating normal sinus rhythm and atrial fibrillation in ECG signal: A phase rectified signal averaging based approach

Abnormal electrical activities in the heart cause various types of arrhythmia or cardiac dysrhythmia. Atrial fibrillation and atrial flutter are most important among them. Automatic detection of different cardiac abnormalities is an emerging field of study in assistive diagnosis technology for cardiac diseases. Atrial fibrillation (AF) is a kind of arrhythmia which increases risk of heart attack especially to the older people. Detection of AF at the early stage may cause prevention of serious stoke. In this paper a new technique based on phase rectified signal averaging (PRSA) is proposed to characterize and classify the AF rhythm from normal. The performance of this method is tested with the MIT-BIH arrhythmia data base and sensitivity and specificity of more than 96% is obtained.