Detection of atrial fibrillation using continuous wavelet transform and wavelet coherence
by Kora Padmavathi; Kalva Sri Ramakrishna
International Journal of Systems, Control and Communications (IJSCC), Vol. 6, No. 4, 2015

Abstract: Atrial fibrillation (AF) is a type of heart ailment that occurs when atria beats quicker than normal to move blood from atria to the ventricles. Our present study proposes a technique to detect AF ECG patterns with the use of continuous wavelet transform (CWT), wavelet coherence (WTC) is presented. The wavelet coherence function finds common frequencies between two signals and evaluates similarity of the two signals. The mother wavelet used is db4. The ECG variation of atrial fibrillation (AF) is observed in lead II of ECG. For the detection of normal and AF beats, WTC output values are given as the input features for the Levenberg-Marquardt neural network (LMNN) classifier. The data was collected from MIT/BIH AF database.

Online publication date: Fri, 16-Oct-2015

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