ECG Signal Denoising Based on Morphological Filtering

Electrocardiographic (ECG) signal are often contaminated with different types of noise and base-line drift. A morphological filtering approach was put forward to remove the noise of the ECG signals and to calibrate the base-line drift in this paper. Different sizes of structuring elements were used to process the signal for different nature of ECG signal and noise. The morphological filtering approach is simple, fast and real-time in processing, and it keeps the ECG signal shape unchanged while removing the noise. An experiment was carried out to simulate the morphological filtering approach with LABVIEW, and it was shown that this approach was effective in removing noise and in calibrating the base-line drift.