  The present work proposes a computer-aided normal and abnormal heart sound
identification based on Discrete Wavelet Transform (DWT), it being useful for
tele-diagnosis of heart diseases. Due to the presence of Cumulative Frequency
components in the spectrogram, DWT is applied on the spectro-gram up to n level
to extract the features from the individual approximation components. One
dimensional feature vector is obtained by evaluating the Row Mean of the
approximation components of these spectrograms. For this present approach, the
set of spectrograms has been considered as the database, rather than raw sound
samples. Minimum Euclidean distance is computed between feature vector of the
test sample and the feature vectors of the stored samples to identify the heart
sound. By applying this algorithm, almost 82% of accuracy was achieved.
