الفهرس 
Anatomy of the heart
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Abstract
For several years, the automatic classification of ECG signals has received great attention from the biomedical engineering community due to the fact that ECG signals provide cardiologists with useful information about the rhythm and functioning of the heart. Analysis of ECG signals has a great importance in the detection of cardiac anomalies. In clinical settings, such as the Intensive Care Unit, it is essential for an automated system to accurately detect and classify ECG signals. The present work aims to investigate the performance of a number of feature extraction techniques, and select an appropriate methodology for the design of an automatic classification system that performs effectively with multiple ECG channels. This thesis organized in eight chapters as follows:
Chapter 1 gives an introduction, aims and thesis organization.
Chapter 2 describes the origin of the ECG signals. In addition, noise artifacts that may contaminate the signal are discussed in this chapter. Also, the required pre-processing steps and data collection are presented.
Chapter 3 gives some concepts for the analysis of ECG signals.
Chapter 4 introduces a discussion for the different techniques used in extracting statistical features fkom ECG signals in time and transform domains.