Cough sound analysis for pneumonia and asthma classification in pediatric population

Amrulloh, Yusuf, Abeyratne, Udantha, Swarnkar, Vinayak and Triasih, Rina (2015). Cough sound analysis for pneumonia and asthma classification in pediatric population. In: David Al-Dabass, Zuwairie Ibrahim, Mohd Ibrahim Shapiai and Athansios Pantelous, Proceedings - 6th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2015. 6th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2015, Kuala Lumpur, Malaysia, (127-131). 9-11 February 2015. doi:10.1109/ISMS.2015.41


Author Amrulloh, Yusuf
Abeyratne, Udantha
Swarnkar, Vinayak
Triasih, Rina
Title of paper Cough sound analysis for pneumonia and asthma classification in pediatric population
Conference name 6th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2015
Conference location Kuala Lumpur, Malaysia
Conference dates 9-11 February 2015
Convener Ibrahim, Zuwairie
Proceedings title Proceedings - 6th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2015
Journal name Proceedings - International Conference on Intelligent Systems, Modelling and Simulation, ISMS
Series Proceedings - International Conference on Intelligent Systems, Modelling and Simulation, ISMS
Place of Publication Los Alamitos, CA United States
Publisher IEEE Computer Society
Publication Year 2015
Year available 2015
Sub-type Fully published paper
DOI 10.1109/ISMS.2015.41
Open Access Status Not Open Access
ISBN 9781479982578
ISSN 2166-0670
2166-0662
Editor David Al-Dabass
Zuwairie Ibrahim
Mohd Ibrahim Shapiai
Athansios Pantelous
Volume 2015-October
Start page 127
End page 131
Total pages 5
Chapter number 25
Total chapters 40
Collection year 2016
Language eng
Abstract/Summary Pneumonia and asthma are the common diseases in pediatric population. The diseases share some similarities of symptoms that make them difficult to separate without the proper diagnostic tools. The majority of pneumonia cases occur in the third world countries wherein even the basic diagnostic tools (e.g.: x-ray) are extremely rare. In these countries, the WHO recommends using rapid breathing and chest in-drawing as approach to diagnose pneumonia in children with cough. As the results, many asthma patients were misdiagnosed as pneumonia and prescribed for unnecessary antibiotic treatment. In this study, we propose a cough sound analysis based method to differentiate pneumonia from asthma. Cough is the major symptom of pneumonia and asthma. Past studies showed the acoustic of cough sounds may carry important information related with the diseases. However, there were no attempts to use cough sounds to separate pneumonia and asthma in pediatric population. Our method extracted sound features such as Mel-frequency cepstral coefficients, non-Gaussianity score and Shannon entropy. The features were then used to develop artificial neural network classifiers. Tested using leave one out validation technique in eighteen subjects, our method achieved sensitivity, specificity and Kappa of 89%, 100%, and 0.89 respectively. The results show the potential of our method to be developed as a tool to differentiate pneumonia from asthma in remote areas.
Keyword Cough sound analysis
Neural network
Pediatrics
Pneumonia
Asthma
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status UQ

 
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