Distinctive features for normal and crackles respiratory sounds using cepstral coefficients

Mohd Johari, Nabila Husna and Abdul Malik, Noreha and Sidek, Khairul Azami (2019) Distinctive features for normal and crackles respiratory sounds using cepstral coefficients. Bulletin of Electrical Engineering and Informatics, 8 (3). pp. 875-881. ISSN 2302-9285

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Abstract

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, Linear Predictive Cepstral Coefficient (LPCC) and Mel-frequency Cepstral Coefficient (MFCC) are 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 statistical computations of the cepstral coefficient of LPCC and MFCC show that the mean LPCC except for the third coefficient and first three statistical coefficient values of MFCC’s SD provide distinctive feature between normal and crackles respiratory sounds. Hence, LPCCs and MFCCs can be used as feature extraction method of respiratory sounds to classify between normal and crackles as screening and diagnostic tool.

Item Type:	Article (Journal)
Additional Information:	3920/73673
Uncontrolled Keywords:	Crackles, LPCC, MFCC, Respiratory sounds, Statistical computation
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:	15 Aug 2019 17:04
Last Modified:	24 Nov 2019 23:35
URI:	http://irep.iium.edu.my/id/eprint/73673

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