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Efficient Artifact Elimination in Cardiac Signals using Variable Step Size Adaptive Noise Cancellers

In this paper several variable step size adaptive filter structures for extracting high resolution electrocardiographic ECG signals are presented which estimates the deterministic components of the ECG signal and removes the artifacts. The noise canceller minimizes the mean square error MSE between the input noisy ECG signal and noise reference. Different noise canceller structures are proposed to remove diverse forms of artifacts: power line interference, baseline wander, muscle artifacts and electrode motion artifacts. The proposed implementation is suitable real time applications, where large signal to noise ratios with fast convergence are required. Simulation studies shows that the proposed realization gives better performance compared to existing realizations in terms of signal to noise ratio, convergence rate and MSE.