The main obstacle in development of intelligent autodiagnosis medical systems based on
the analysis of phonocardiography (PCG) signals is noise. The noise can be caused by …

Signal denoising remains to be one of the main problems in the field of signal processing.
Various signal denoising algorithms using wavelet transforms have been introduced …

This paper focuses on the denoising of phonocardiogram (PCG) signals by means of
discrete wavelet transform (DWT) using different wavelets and noise level estimation …

Segmentation of the phonocardiography (PCG) signal into cardiac cycles is a primary task
for the diagnosis of cardiovascular diseases. However, PCG is highly susceptible to noise …

Wavelet-based (WT) denoising has been frequently used as simple and efficient method
enabling high signal-to-noise ratio. Moreover, by using second generation WT and lifting …

Phonocardiograms (PCGs), recording of heart sounds, have many advantages over
traditional auscultation in that they may be replayed and analyzed for spectral and frequency …

Cardiovascular pathologies cause 23.5% of human deaths, worldwide. An auto-diagnostic
system monitoring heart activity, which can identify the early symptoms of cardiac illnesses …

Phonocardiograms (PCGs), recordings of heart sounds, have many advantages over
traditional auscultation in that they may be replayed and analysed for spectral and frequency …

The various noise components make the diagnostic evaluation of phonocardiographic
records difficult or in some cases even impossible. This paper presents a novel wavelet …

Phonocardiograms (PCG) are recordings of the acoustic waves produced by the mechanical
action of the heart. They generally consist of two kinds of acoustic vibrations: heart sounds …