Content-based classification of breath sound with enhanced features

Lei, Baiying, Rahman, Shah Atiqur, and Song, Insu (2014) Content-based classification of breath sound with enhanced features. Neurocomputing, 141. pp. 139-147.

[img] PDF (Published Version) - Published Version
Restricted to Repository staff only

[img] PDF (Author's Accepted Version) - Accepted Version
Restricted to Repository staff only

View at Publisher Website: http://dx.doi.org/10.1016/j.neucom.2014....
 
20
13


Abstract

Since breath sound (BS) contains important indicators of respiratory health and disease, analysis and detection of BS has become an important topic, with diagnostic and assessment of treatment capabilities. In this paper, the identification and classification of respiratory disorders based on the enhanced perceptual and cepstral feature set (PerCepD) is proposed. The hybrid PerCepD feature can capture the time-frequency characteristics of BS very well. Thus, it is very effective for the exploration and classification of normal and pathological BS related data. The classification models based on support vector machine (SVM) and artificial neural network (ANN) have been adopted to achieve automatic detection from BS data. The high detection accuracy results validate the performance of the proposed feature sets and classification model. The experimental results also demonstrate that the high accuracy of the pathological BS data can provide reliable diagnostic suggestions for breath disorders, such as flu, pneumonia and bronchitis.

Item ID: 32851
Item Type: Article (Refereed Research - C1)
Keywords: breath sound; content-based classification; support vector machine; artificial neural network
ISSN: 1872-8286
Funders: Bill & Melinda Gates Foundation, China Postdoctoral Science Foundation, National Natural Science Foundation of Guangdong Province
Projects and Grants: Bill & Melinda Gates Foundation OPP1032125, China Postdoctoral Science Foundation project 2013M540663, National Natural Science Foundation of Guangdong Province S2013040014448
Date Deposited: 25 Jun 2014 00:06
FoR Codes: 08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining @ 100%
SEO Codes: 92 HEALTH > 9202 Health and Support Services > 920203 Diagnostic Methods @ 100%
Downloads: Total: 13
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page