Paper Info
Title
Evaluation Of Mel-Frequency Cepstrum For Wheeze Analysis
Abstract
Monitoring of wheezes is an integral part of managing Chronic Respiratory Diseases such as asthma and Chronic Obstructive Pulmonary Disease (COPD). Recently, there is a growing interest in automatic detection of wheezes and the use of Mel-Frequency Cepstral Coefficients (MFCC) have been shown to achieve encouraging detection performance. While the successful use of MFCC for identifying wheezes has been demonstrated, it is not clear which MFCC coefficients are actually useful for detecting wheezes. The objective of this paper is to characterize and study the effectiveness of individual coefficients in discriminating between wheezes and normal respiratory sounds. The coefficients have been evaluated in terms of histogram dissimilarity and linear separability. Further, a comparison between the use of single coefficient against other combinations of coefficients is also presented. The results demonstrate MFCC-2 coefficient to be significantly more effective than all the other coefficients in discriminating between wheezes and normal respiratory sounds sampled at 8000 Hz.
Year
DOI
Venue
2019
10.1109/EMBC.2019.8857848
2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Keywords
Field
DocType
Lung sound, wheeze, Mel-frequency cepstral coefficient, classification, low-complexity
Linear separability,Computer vision,Mel-frequency cepstrum,Histogram,Normal respiratory sounds,Computer science,Speech recognition,Artificial intelligence,Wheeze
Conference
Volume
ISSN
Citations 
2019
1557-170X
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Renard Xaviero Adhi Pramono100.68
Syed Anas Imtiaz2226.03
Esther O. Rodríguez-Villegas3247.08