DETECTION OF ARTIAL FIBRILLATION DISORDER BY ECG USING DISCRETE WAVELET TRANSFORMS

Abstract

Atrial fibrillation (A-fib) is the most common cardiac disorder. To efficiently treat or inhibit, an automatic detection based on electrocardiograph (ECG)
monitoring is significantly required. ECG is a key function in the analysis of the heart functioning and diagnostic of diseases. Currently, a computer based
system is used to analyze the ECG signal. The main aim of this project is to analyze a heart malfunctions named as A-fib, using discrete wavelet transforms
(DWT). The ECG signals were decomposed into time-frequency representations using DWT, and the statistical features were calculated to describe their
distribution. The DWT detailed coefficients are used to obtain various parameters of the ECG signal such as the mean, variance, standard deviation, and
entropy of the signal. An analysis had been made with these parameters of various patients with normal heart functioning and A-fib to identify the disorder.
Keywords: Atrial fibrillation, Electrocardiogram, Discrete wavelet transforms.