Filtering and classification of phonocardiogram signals using wavelet transform.
Auscultation is a technique in which a stethoscope is used to listen to the sounds of the heart. Structural defects of the heart are often reflected in the sounds the heart produces, and auscultation provides clinicians with valuable diagnostic and prognostic information. Although heart sound analysis by auscultation is convenient as clinical tool, it is difficult to analyse heart sound signals in the time or frequency domain. Thus phonocardiogram (PCG), recording of heart sounds has many advantages over traditional auscultation, in that they may be replayed and analysed for time and frequency information. Using discrete wavelet transform, the signal is decomposed and reconstructed without significant loss of information in the signal content. The error of rebuilding can be considered as an important parameter in the classification of the pathological severity of the phonocardiogram signals. Variation of this parameter is very sensitive to the murmur importance in PCG signals.
Debbal
S M
SM
Genie Biomedical Laboratory (GBM), Department of Electronic, Faculty of Science Engineering, University Aboubekr Belkaid, Tlemcen, Algeria. adebbal@yahoo.fr
Bereksi-Reguig
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D000465:Algorithms; D006337:Heart Murmurs / Q000175:diagnosis / Q000503:physiopathology; D006801:Humans; D010701:Phonocardiography / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted