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ECG Morphological Marking using Discrete Wavelet Transform

Electrocardiogram (ECG) is almost recurrent signals that express the activity of the heart. A large amount of information on the normal and pathological physiology of heart can be acquired from ECG. However, the ECG signals being nonstationary in nature, it is very hard to visually examine them. Thus the need is there for computer built methods for ECG signal analysis. This paper has been stimulated by the need to find an effective method for ECG signal analysis which is common and has excellent accuracy and minimum computation time. The initial task for efficient analysis is the removal of noise. It actually involves the extraction of the needed cardiac components by degeneration of the background noise. Enhancement of signal is attained by the use of multi-resolution feature extraction using DWT decomposition method. Use of this was influenced by its adaptive nature. The second task is that of P, QRS complex and T wave peak detection which is performed by the use of multi-resolution adaptive threshold method executed with DWT. The experiments are carried out on MIT-BIH database and PTB diagnostic ECG database. The results show the proposed method is very effective and an efficient method for computation of P, QRS complex and T wave peak detection.