Classification of respiratory sounds by using an artificial neural network

被引：0

作者：

Sezgin, MC ^{[1
]}

Dokur, Z ^{[1
]}

Ölmez, T ^{[1
]}

Korürek, M ^{[1
]}

机构：

[1] Istanbul Tech Univ, Dept Elect & Commun Engn, TR-80626 Istanbul, Turkey

来源：

PROCEEDINGS OF THE 23RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-4: BUILDING NEW BRIDGES AT THE FRONTIERS OF ENGINEERING AND MEDICINE | 2001年 / 23卷

关键词：

respiratory sounds; classification of biomedical signals; artificial neural network;

D O I：

暂无

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

In this paper, a classification method for respiratory sounds (RSs) in patients with asthma and in healthy subjects is presented. Wavelet transform is applied to a window containing 256 samples. Elements of the feature vectors are obtained from the wavelet coefficients. The best feature elements are selected by using dynamic programming. Grow and Learn (GAL) neural network is used for the classification. It is observed that RSs of patients (with asthma) and healthy subjects are successfully classified by the GAL network.

引用

页码：697 / 699

页数：3

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