Feature extraction for the differentiation of dry and wet cough soundsPublic Deposited
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Cough is one of the most common symptoms in all respiratory diseases. It is important to provide the healthcare professionals with useful clinical information such as frequency, severity and nature of cough to have a better diagnosis and hence better treatment. The main objective of this thesis is to analyze cough sounds and extract features that can differentiate dry and wet cough sounds. This thesis proposes two features to achieve this goal. The first feature is the number of peaks of the energy envelope of the cough signal. The second feature is the power ratio of two frequency bands of the second phase of the cough signal. A set of nine highly dry and eight highly wet cough recordings were used in this thesis. Using these two features, a clear separation was observed among the dry and wet cough recordings. Furthermore, a Graphical User Interface (GUI) was designed in this thesis as a tool to analyze the cough signals in both time and frequency domain.
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- Copyright © 2011 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.
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