International Journal of Computational Intelligence Systems

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Volume 9, Issue 4, August 2016, Pages 595 - 611

Identification of Pulmonary Disorders by Using Different Spectral Analysis Methods

Authors
F. Z. Göğüş1, *, fzehra@selcuk.edu.tr, B. Karlık2, bekirkarlik@beykent.edu.tr, G. Harman3, gunes.guclu@yalova.edu.tr
1Department of Computer Engineering, Selcuk University, Konya, 42075, Turkey
2Faculty of Engineering and Architecture, Beykent University, Istanbul, Turkey
3Department of Computer Engineering, Yalova University, Yalova, 77100, Turkey
*Corresponding Author: fzehra@selcuk.edu.tr
Corresponding Author
F. Z. Göğüşfzehra@selcuk.edu.tr
Received 1 September 2015, Accepted 1 March 2016, Available Online 1 August 2016.
DOI
10.1080/18756891.2016.1204110How to use a DOI?
Keywords
Artificial Neural Network; Classification Accuracy; Feature Extraction; Power Spectrum Density; Spectral Analysis
Abstract

This study presents detection of pulmonary disorders using different spectral analysis methods such as fast Fourier transform, autoregressive and the autoregressive moving average. Power spectral densities of the sounds were estimated through these methods. Feature vectors were constructed by extracting statistical features from the PSDs. Created feature vectors were used as inputs into the artificial neural networks. Then performances of spectral analysis methods were compared according to classification accuracies, sensitivities and specificities. In this aspect, the study is a comparative study of different spectral analysis methods.

Copyright
© 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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Next Article In Issue>
Journal
International Journal of Computational Intelligence Systems
Volume-Issue
9 - 4
Pages
595 - 611
Publication Date
2016/08/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.1080/18756891.2016.1204110How to use a DOI?
Copyright
© 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - F. Z. Göğüş
AU  - B. Karlık
AU  - G. Harman
PY  - 2016
DA  - 2016/08/01
TI  - Identification of Pulmonary Disorders by Using Different Spectral Analysis Methods
JO  - International Journal of Computational Intelligence Systems
SP  - 595
EP  - 611
VL  - 9
IS  - 4
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2016.1204110
DO  - 10.1080/18756891.2016.1204110
ID  - Göğüş2016
ER  -