Feature extraction based on mel-scaled wavelet transform for heart sound analysis.
To provide a robust representation of heart sound signal in an automatic heart disease diagnosis system, a melscaled wavelet transform has been developed. It combines the advantages of linear perceptual scale by mel mapping with the suitability of analyzing non-stationary signals by wavelet transform. The heart sound signal is firstly divided into windowing frames. A set of mel-scaled filterbank is then used to calculate the mel-warped spectrum, which is followed by a wavelet transform to extract the mel-scaled wavelet features. The performance of the proposed algorithm is evaluated for heart sound analysis using clean and noisy data, and compared with the standard mel-frequency cepstral coefficients. Results show that the proposed approach provides a robust representation of heart sound signal in noisy environment.
Wang
P
P
BioMedical Engineering Research Centre, Nanyang Technological University, Singapore.
Kim
Y
Y
Soh
C
C