Mathematical Morphology and the Heart Signals

Abstract

Nowadays, signal processing is integrated into most systems for analyzing and interpreting ECG and PCG signals. Its objectives are multiple and mainly include compensating for the addition of artifacts to the signals of interest, and extracting information that is not visible by direct visual analysis. Considering that useful clinical information is found in the characteristic waves of the ECG, in particular, the P wave, the QRS complex, the T wave and the heart sounds of the PCG signal. These signals provide important indicators for the diagnosis of heart disease because they reflect physiological processes. These are non-stationary signals that are very sensitive to noise, hence the need to have optimal conditions to record them. It is necessary to use appropriate signal processing tools for noise suppression and wave detection of the ECG signal. Our method uses Morphological filtering, multi-scale morphological and the other by top-hat transform, which are based on mathematical morphology. The latter is based on mathematical operators called opening and closing morphology operators. These methods are also tested, with the aim of removing the noise and detection of the waves of the ECG signal and of the pathological sounds of the PCG signal.