Effective Reconstruction of the Cardiac Signal Using Adaptive Noise Cancellers

An electrocardiogram (ECG) is a graphical representation of the sequence of myocardial depolarization and repolarization. In some emergency cases the ECG signal can be obtained in the ambulance itself and it has to be transmitted to the clinic. During the transmission the tiny features of the ECG signal are masked due to channel noise. In addition to these the signal may get disturbed by some artifacts like power line interference (PLI), base line wander (BW), muscle artifacts (MA), and electrode motion artifacts (EM) etc,. These artifacts strongly affect the ST segment of the signal and degrade the signal quality. In this situation the doctor may give the wrong diagnosis to the patient. So the electrocardiogram (ECG) signal needs to be pre-processed. In this paper we are going to present various adaptive noise cancellers (ANC) based on variable step-sized algorithm. Adaptive filter is a primary method to filter the ECG signal. Here the main interest is to reduce the affect of PLI and BW artifacts using different algorithms like Variable Step Size Least Mean Squares (VSS- LMS), VSS-Normalized LMS (VSS-NLMS), VSS Signed Regressor LMS (VSS-SRLMS), VSS Signed LMS (VSS-SLMS) and VSS Sign-Sign LMS (VSS-SSLMS) to decide which can give the good results with less computational complexity.

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