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Distinctive features for classification of respiratory sounds between normal and crackles using cepstral coefficients

Mohd Johari, Nabila Husna and Abd Malik, Noreha and Sidek, Khairul Azami (2018) Distinctive features for classification of respiratory sounds between normal and crackles using cepstral coefficients. In: 2018 7th International Conference on Computer and Communication Engineering (ICCCE), 19th-20th September 2018, Kuala Lumpur.

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Classification of respiratory sounds between normal and abnormal is very crucial for screening and diagnosis purposes. Lung associated diseases can be detected through this technique. With the advancement of computerized auscultation technology, the adventitious sounds such as crackles can be detected and therefore diagnostic test can be performed earlier. In this paper, Mel-frequency Cepstral Coefficient (MFCC) is used to extract features from normal and crackles respiratory sounds. By using statistical computation such as mean and standard deviation (SD) of cepstral based coefficients it can differentiate between crackles and normal sounds. The result shows that the first three statistical values of SD of coefficients provide distinctive feature between normal and crackles respiratory sounds. Hence, MFCCs can be used as feature extraction method of respiratory sounds to classify between normal and crackles as screening and diagnostic tool.

Item Type: Conference or Workshop Item (Plenary Papers)
Additional Information: 3920/67988
Uncontrolled Keywords: MFCC, crackles sound, features, statistical computation and respiratory sounds
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering
Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User: Assoc Prof Dr Khairul Azami Sidek
Date Deposited: 05 Dec 2018 14:47
Last Modified: 17 Aug 2019 11:50
URI: http://irep.iium.edu.my/id/eprint/67988

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