Open AccessA New Recongnition System Based on Gabor Wavelet Transform for Shockable Electrocardiograms
Author(s) -
Takayuki Okai,
Shonosuke Akimoto,
Hidetoshi Oya,
Kazushi Nakano,
Hiroshi Miyauchi,
Yoshikatsu Hoshi
Publication year - 2021
Publication title -
journal of applied life sciences international
Language(s) - English
Resource type - Journals
ISSN - 2394-1103
DOI - 10.9734/jalsi/2020/v23i1230203
Subject(s) - pattern recognition (psychology) , artificial intelligence , feature (linguistics) , wavelet transform , gabor transform , computer science , wavelet , computer vision , time–frequency analysis , philosophy , linguistics , filter (signal processing)
This paper presents a new recognition system for shockable arrhythmias for patients suffering from sudden cardiac arrest. In order to develop the recognition system, lots of electrocardiogram (ECGs) have been analyzed by using gabor wavelet transform (GWT). Although, there is a huge number of spectrum feature parameters, recognition performance for all combinations for spectrum feature parameters are evaluated, and on the basis of the evaluation results, useful and effective spectrum features for ECGs are extracted. As a result, the proposed recognition system based on the selected effective spectrum feature parameters can achieved good performance comparing with the existing results.