Abnormality Detection from ECG Signals Using Multiscale Wavelet Analysis

Abstract

Cardiovascular disease is the number one cause of mortality in the western world, responsible for more than 16 million deaths annually worldwide. It can be diagnosed from Electro Cardiogram (ECG) signal, which captures the cardiac activities of the heart. Such signal apart of a large volume and velocity is often characterised by low quality due to the noise and other artefacts. In order to extract features from the ECG signal and perform the classication preprocessing, noise removal is required and it plays an important role in correct feature extraction and classication. Despite the signicant attention devoted in literature to preprocessing, feature extraction and classication of ECG signal, the accuracy is still the main concern, which could be one of the reasons why medical practitioners have not yet accepted system recommendations in their diagnosis. This is clear indication that the additional work is required.