Title :
Feature extraction for the differentiation of dry and wet cough sounds
Author :
Chatrzarrin, Hanieh ; Arcelus, Amaya ; Goubran, Rafik ; Knoefel, Frank
Author_Institution :
Dept. of Syst. & Comput. Eng., Carleton Univ., Ottawa, ON, Canada
Abstract :
Differentiating dry and wet cough is an important factor in respiratory disease. The main objective of this paper is to analyze cough sounds and extract features that can be used in differentiation of dry and wet cough sounds. This paper 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 eight highly dry and eight highly wet cough sound recordings were used. Using these two features, a clear separation was observed among the dry and wet cough sound recordings.
Keywords :
acoustic signal processing; diseases; feature extraction; medical signal processing; patient diagnosis; pneumodynamics; signal classification; cough signal energy envelope peaks; cough signal second phase; cough sound differentiation; dry cough sounds; feature extraction; frequency band power ratio; respiratory disease; wet cough sounds; Band pass filters; Diseases; Feature extraction; Filtering algorithms; Low pass filters; Monitoring; Spectrogram; biomedical signal processing; cough analysis; dry cough; feature extraction; signal processing algorithms; wet cough;
Conference_Titel :
Medical Measurements and Applications Proceedings (MeMeA), 2011 IEEE International Workshop on
Conference_Location :
Bari
Print_ISBN :
978-1-4244-9336-4
DOI :
10.1109/MeMeA.2011.5966670