Using Back-Propagation Neural Network for Automatic Wheezing Detection

Bor Shing Lin, Huey Dong Wu, Sao Jie Chen, Gene Eu Jan, Bor-Shyh Lin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This study describes the design of a fast and high performance wheeze recognition system. The proposed wheezing detection algorithm is based on order truncate average (OTA) and back-propagation neural network (BPNN). Some features are then extracted from the processed spectra to train a BPNN. Eventually, the new testing samples go through the trained BPNN to recognize whether they are wheezing sounds. Experimental results show a high sensitivity of 0.946 and a specificity of 1.0 in qualitative analysis of wheeze recognition.

Original languageEnglish
Title of host publicationProceedings - 2015 International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2015
EditorsJeng-Shyang Pan, Ching-Yu Yang, Hsiang-Cheh Huang, Ivan Lee
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages49-52
Number of pages4
ISBN (Electronic)9781509001880
DOIs
StatePublished - 19 Feb 2016
Event11th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2015 - Adelaide, Australia
Duration: 23 Sep 201525 Sep 2015

Publication series

NameProceedings - 2015 International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2015

Conference

Conference11th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2015
CountryAustralia
CityAdelaide
Period23/09/1525/09/15

Keywords

  • asthma
  • back-propagation neural network
  • bilateral filtering
  • order truncate average
  • wheezing detection

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