International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
Volume 66 - Issue 17 |
Published: March 2013 |
Authors: A. E. El-Alfi, A. F. Elgamal, R. M. Ghoniem |
![]() |
A. E. El-Alfi, A. F. Elgamal, R. M. Ghoniem . A Computer-based Sound Recognition System for the Diagnosis of Pulmonary Disorders. International Journal of Computer Applications. 66, 17 (March 2013), 22-30. DOI=10.5120/11176-6331
@article{ 10.5120/11176-6331, author = { A. E. El-Alfi,A. F. Elgamal,R. M. Ghoniem }, title = { A Computer-based Sound Recognition System for the Diagnosis of Pulmonary Disorders }, journal = { International Journal of Computer Applications }, year = { 2013 }, volume = { 66 }, number = { 17 }, pages = { 22-30 }, doi = { 10.5120/11176-6331 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2013 %A A. E. El-Alfi %A A. F. Elgamal %A R. M. Ghoniem %T A Computer-based Sound Recognition System for the Diagnosis of Pulmonary Disorders%T %J International Journal of Computer Applications %V 66 %N 17 %P 22-30 %R 10.5120/11176-6331 %I Foundation of Computer Science (FCS), NY, USA
This paper presents a computer-based sound recognition system for diagnosis of pulmonary disorders based on the interpretation of the lung sound signals (LSS). We propose a novel method of analysis of LSS using the Mel-frequency cepstral coefficients, the spectral and temporal parameters estimated from the frequency subbands of the discrete wavelet transform. A Linde Buzo Gray (LBG) clustering neural network model is developed for classifying the LSS to one of the six categories: normal, wheeze, crackle, squawk, stridor, or rhonchus. Experimental results demonstrate the effectiveness of the proposed system in detecting pulmonary disorders.