Analysis of Signal Processing Techniques to Identify Cardiac Disorders

Abstract: World Health Organization (WHO) report says that most of the countries have highest incidence of heart related diseases.If no initiative is taken to check the disease that is the most predictable and preventable among all chronic diseases people around the world will have to suffer due to massive heart attack problem.The Electrocardiogram (ECG) is an important bio-signal representing the electrical activity of the heart. It contains important insight into the state of health and nature of the disease afflicting the heart. Processing of cardiac signal and identifying the cardiac disorders is challenging task in biomedical signal processing. This paper deals with different signal processing techniques that are widely in use for determining what sort of a cardiovascular problem a patient is suffering from. Time domain, Frequency domain and Principal Component Analysis have been done on the ECG with the final goal of understanding which of these methods is the best for the identification of cardiac arrhythmias such as Atrial Fibrillation (AF), Cardiac Ischemia (CI) and Sudden Cardiac Arrest (SCA). ECG data has been obtained from the MIT-BIH cardiac arrhythmia database. The work has been done using MATLAB®.

Keywords: Normal sinus rhythm (NSR), Atrial fibrillation (AF), Cardiac Ischemia (CI), Sudden Cardiac Arrest (SCA).