DocumentCode
1264531
Title
Comparison of discrete wavelet and Fourier transforms for ECG beat classification
Author
Dokur, Z. ; Ölmez, T. ; Yazgan, E.
Author_Institution
Dept. of Electron. & Commun. Eng., Istanbul Tech. Univ., Turkey
Volume
35
Issue
18
fYear
1999
fDate
9/2/1999 12:00:00 AM
Firstpage
1502
Lastpage
1504
Abstract
Two feature extraction methods, Fourier and wavelet analyses for ECG beat classification, are comparatively investigated. ECG features are searched by dynamic programming according to the divergence values. 10 types of ECG beat from an MTT-BIH database are classified with a success of 97% using a restricted Coulomb energy neural network trained by genetic algorithms
Keywords
discrete Fourier transforms; discrete wavelet transforms; dynamic programming; electrocardiography; feature extraction; genetic algorithms; medical signal processing; neural nets; signal classification; Coulomb energy neural network; ECG beat classification; MTT-BIH database; discrete Fourier transform; discrete wavelet transform; dynamic programming; feature extraction; genetic algorithm;
fLanguage
English
Journal_Title
Electronics Letters
Publisher
iet
ISSN
0013-5194
Type
jour
DOI
10.1049/el:19991095
Filename
802761
Link To Document