Segmented Modeling of ECG Signal by Using Hermite Basis Function

In this paper, a new technique of modeling for the approximation of entire ECG signal is presented. The proposed method is applied on four different ECG beats. In most modeling methods, best approximation for the important part of the signal is done. But the entire ECG signal is important for the diagnosis of different diseases. The proposed method exploit the importance of whole ECG waves by performing a segmented based modeling using Hermite basis function. The presented method uses only the 5th order Hermite basis functions which considerably reduce the total parameters needed to represent the ECG signal in comparison with other Hermitian based methods. As the result shows the total error obtained in this method is very less than in comparison with similar non segmented method by using only 5th order of Hermite basis function. And the result shows that the segmented modeling method could keep the ECG information without distortion. This has a great impact in modeling the heart arrhythmias where a small error could mislead the diagnosis. Index term – Hermite basis functions, Segmented modeling, Electrocardiography signal Introduction Biomedical signals are fundamental observations for analyzing the body function and for diagnosing a wide spectrum of diseases. One of the most common causes of death in the world is cardiac abnormalities namely heart attacks, raised blood pressure (hypertension), peripheral artery disease, congenital heart disease and heart failure. So there is a need to model the ECG signal which is helpful for diagnosis. Modeling the signal is mainly concerned with making the best approximation of the signal followed by obtaining the parameters of the model to be used for arrhythmia classification. It is expected that more accurate model parameters obtained during this process will make the classifier more reliable in detecting morphological based arrhythmias. These methods are mainly focused with approximation of the entire ECG beat without paying attention to the importance of the intervals of the signal which is the case for vital signals. As can be seen from Fig.1, a schematic representation of the normal ECG beat consists of three main parts named as P, QRS, and T waves which are the most important factors in heart arrhythmia diagnosis. Therefore, it