Imperial College London
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Dr Renard Xaviero Adhi Pramono

Faculty of Engineering, Department of Electrical and Electronic Engineering

Research Associate
 
 
 
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Contact

 

renard.pramono14 Website

 
 
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Location

 

907Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Pramono:2019:10.1109/EMBC.2019.8857848,
author = {Pramono, RXA and Imtiaz, SA and Rodriguez-Villegas, E},
doi = {10.1109/EMBC.2019.8857848},
pages = {4686--4689},
publisher = {IEEE},
title = {Evaluation of mel-frequency cepstrum for wheeze analysis},
url = {http://dx.doi.org/10.1109/EMBC.2019.8857848},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - 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.
AU  - Pramono,RXA
AU  - Imtiaz,SA
AU  - Rodriguez-Villegas,E
DO  - 10.1109/EMBC.2019.8857848
EP  - 4689
PB  - IEEE
PY  - 2019///
SN  - 1557-170X
SP  - 4686
TI  - Evaluation of mel-frequency cepstrum for wheeze analysis
UR  - http://dx.doi.org/10.1109/EMBC.2019.8857848
UR  - https://www.ncbi.nlm.nih.gov/pubmed/31946908
UR  - https://ieeexplore.ieee.org/document/8857848
UR  - http://hdl.handle.net/10044/1/77541
ER  -
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