A Survey on Classification of ECG Signal Study

Abstract

Electrocardiogram (ECG) is a non-linear dynamic signal which plays the main role in diagnosis heart diseases. Classification of ECG signal is one of the most important reason of diagnosing the heart diseases. Detecting accurate ECG signal not only the most difficult task but also classifying heart signal is very difficult task. There are many types of classifiers are available for ECG classification. The most popular classifier that used in ECG classification is Artificial Neural Network (ANN) and in second degree is Support Vector Machine (SVM). In this paper, we discuss a survey of preprocessing, ECG database, feature extraction and classifiers. This paper also discusses background of Electrocardiogram, evaluation matrices of classifiers and issues of classifiers.