Multidatabase ECG signal processing

Abstract

An Electrocardiogram (ECG) records the electrical activity of the heart to locate the abnormalities. ECG signal processing is an emerging tool for the cardiologists in medical diagnosis for effective treatments. Many researches focus on how to improve preprocessing and processing algorithms in order to classify ECG signals with low cost and high accuracy. These algorithms consist of removing all types of noise that contaminate the ECG recording as well as extracting the most important features. In this paper, we present a useful Matlab GUI to analyze and classify ECG signal using efficient preprocessing and processing techniques. These techniques allow acquiring ECG recorders from various universal cardiac databases, filtering them using Butterworth low pass filter and IIR notch filter and extracting the most important cardiac features based on discrete wavelet transform db6.