Distinctive features for normal and crackles respiratory sounds using cepstral coefficients
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 detect...
Main Authors: | Mohd Johari, Nabila Husna, Abdul Malik, Noreha, Sidek, Khairul Azami |
---|---|
Format: | Article |
Language: | English English |
Published: |
Universitas Ahmad Dahlan
2019
|
Subjects: | |
Online Access: | http://irep.iium.edu.my/73673/ http://irep.iium.edu.my/73673/ http://irep.iium.edu.my/73673/ http://irep.iium.edu.my/73673/1/73673_Distinctive%20features%20for%20normal.pdf http://irep.iium.edu.my/73673/7/73673_Distinctive%20features%20for%20normal%20and%20crackles%20respiratory%20sounds%20using%20cepstral%20coefficients_Scopus.pdf |
Similar Items
-
Distinctive features for classification of respiratory sounds between normal and crackles using cepstral coefficients
by: Mohd Johari, Nabila Husna, et al.
Published: (2018) -
Classification of normal and crackles respiratory sounds into healthy and lung cancer groups
by: Abdul Malik, Noreha, et al.
Published: (2018) -
On the comparison of line spectral frequencies and mel-frequency cepstral coefficients using feedforward neural network for language identification
by: Gunawan, Teddy Surya, et al.
Published: (2018) -
EEG emotion recognition using features of Mel Frequency Cepstral Coefficients
by: Othman, Marini, et al.
Published: (2011) -
ECG biometric recognition in different physiological conditions using robust normalized QRS complexes
by: Sidek, Khairul Azami, et al.
Published: (2012)