Classification of Normal and Abnormal Lung Sounds Using Wavelet Coefficients - Uysal, Sinem; Uysal, Husamettin; Bolat, Bulent; Yildirim, Tulay (IEEE, 2014)
Auscultation and analysing of lung sound is widely used in clinical area for diagnosis of lung diseases. Due to the non-stationary nature of lung sounds conventional frequency analysis technique is not a successful method for respiratory sound analysis. In this paper, classification of normal and abnormal lung sound using wavelet coefficient intended. Respiratory sounds are decomposed into the frequency sub-bands using wavelet transform and a set of statistical features are inspected from the sub-bands. Then, lung sounds classified as normal and abnormal using these statistical features. Artificial neural network and support vector machine are used for classification process.
Keywords: respiratory sounds; wavelet coefficient; artificial neural network; support vector machine; Engineering; Telecommunications