Detection of Life Threatening ECG Arrhythmias Using Morphological Patterns and Wavelet Transform Method

Abstract

The work in this paper is to investigate the detection of another group of arrhythmias, which might not need immediate attention but may be life threatening that can lead to fatal cardiovascular diseases. The Electrocardiogram plays an imperative role to diagnose such cardiac diseases. But recorded ECG often contaminated by various noises and artifacts. Hence, for accurate diagnosis of heart disease and characterization of normal rhythm from arrhythmic wave, first step is to obtain clear ECG. The proposed method de-noised ECG signal using wavelet transform and extract dynamic features and morphological patterns of ECG arrhythmia. Numerical simulation of statistical parameters proves de-noising capability of proposed method.