Nowadays the use of technology as an aid to medical diagnosis it is part of the routine day-to-day health care provided in hospitals and the outcomes of the use of these technologies in health assistance undoubtedly increased the quality of medical assistance. However even in cases where a detailed clinical examination can provide enough reliable information to the correct diagnosis, diagnostic tests have assumed an overvalued role in clinical practice, thus increasing health care costs.
Classical cardiac auscultation is a powerful clinical tool that, despite having some limitations, may be enhanced by the acquisition, storage and processing of the phonocardiogram (PCG) signal and their functional characterization by the use of cardiac sounds and its features in a quantitative way.
In this work the normal PCG characterization, using the Hilbert-Huang Transform, is presented allowing to the identification of quantitative features, and to use these markers in the cardiac dysfunction analysis by PCG in heart diseases. This characterization will characterize normal markers of cardiac function whose comparison with pathological sounds will contribute to establish a low-cost evaluation in cardiovascular Medicine.