Respiratory diseases such as pneumonia, bronchitis leading causes of child death in the word .out of this pneumonia are causing the million children death each year around the word. One of the challenged faced in consistent diagnosis of childhood pneumonia in secluded area is difficulties arising from field deployable, laboratory facilities and trained healthcare worker. Such issue we address in this paper and to categorize the pneumonia using the geometrical analysis of cough sound. We used the wavelet-based mathematical tool which is a useful work for crackle detection in lung sound analysis. Such feature can be added among new mathematical feature and to develop the automated classifier to distinguish the pneumonia with other respiratory diseases. In our project uses feed forward neural network classifier to increase the classification performance with having sensitivity 90%, specificity 98.7% and accuracy 97%.Cough and crackle sound are sign of pneumonia. Cough sounds permit us for pneumonia diagnosis with adequate sensitivity and specificity.
Keywords:- Slant Wavelet Transform, Neural Network, Pneumonia Cough Sample Sound.