Respiratory sound classification using cepstral features and support vector machine
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IEEE Conference Publications
2014
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| Online Access: | http://dspace.unimap.edu.my:80/dspace/handle/123456789/33429 |
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my.unimap-334292014-04-05T10:09:56Z Respiratory sound classification using cepstral features and support vector machine Palaniappan, Rajkumar Sundaraj, Kenneth, Prof. Dr. prkmect@gmail.com kenneth@unimap.edu.my Respiratory sound MFCC Support vector machine Confusion matrix Link to publisher's homepage at http://ieeexplore.ieee.org/ Respiratory sound analysis provides vital information of the present condition of the Lungs. It can be used to assist medical professionals in differential diagnosis. In this paper, we intend to distinguish between normal (without any pathological condition), airway obstruction pathology and parenchymal pathology using respiratory sound recordings taken from RALE database. The proposed method uses Mel-frequency cepstral coefficients (MFCC) as features extracted from respiratory sounds. The extracted features are distinguished using support vector machine classifier (SVM). The classifier performance is analysed by using confusion matrix technique. A mean classification accuracy of 90.77% was reported using the proposed method. The performance analysis of the SVM classifier using confusion matrix revealed that normal, airway obstruction and parenchymal pathology are classified at 94.11%, 92.31% and 88.00% classification accuracy respectively. The analysis reveals that the proposed method shows promising outcome in distinguishing between the normal, airway obstruction and parenchymal pathology. 2014-04-05T10:09:56Z 2014-04-05T10:09:56Z 2013 Working Paper IEEE Recent Advances in Intelligent Computational Systems, 2013, pages 132-136 http://dspace.unimap.edu.my:80/dspace/handle/123456789/33429 en IEEE Conference Publications |
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Malaysia |
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Universiti Malaysia Perlis |
| content_source |
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http://dspace.unimap.edu.my/ |
| language |
English |
| topic |
Respiratory sound MFCC Support vector machine Confusion matrix |
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Respiratory sound MFCC Support vector machine Confusion matrix Palaniappan, Rajkumar Sundaraj, Kenneth, Prof. Dr. Respiratory sound classification using cepstral features and support vector machine |
| description |
Link to publisher's homepage at http://ieeexplore.ieee.org/ |
| author2 |
prkmect@gmail.com |
| author_facet |
prkmect@gmail.com Palaniappan, Rajkumar Sundaraj, Kenneth, Prof. Dr. |
| format |
Working Paper |
| author |
Palaniappan, Rajkumar Sundaraj, Kenneth, Prof. Dr. |
| author_sort |
Palaniappan, Rajkumar |
| title |
Respiratory sound classification using cepstral features and support vector machine |
| title_short |
Respiratory sound classification using cepstral features and support vector machine |
| title_full |
Respiratory sound classification using cepstral features and support vector machine |
| title_fullStr |
Respiratory sound classification using cepstral features and support vector machine |
| title_full_unstemmed |
Respiratory sound classification using cepstral features and support vector machine |
| title_sort |
respiratory sound classification using cepstral features and support vector machine |
| publisher |
IEEE Conference Publications |
| publishDate |
2014 |
| url |
http://dspace.unimap.edu.my:80/dspace/handle/123456789/33429 |
| _version_ |
1643797185369735168 |