Gabor feature extraction for electrocardiogram signals

Gwo Giun Lee, Jhen Yue Hu, Chun Fu Chen, Huan Hsiang Lin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper, the useful features for clinical diagnosis from electrocardiogram (ECG) signals have been extracted to speed up the diagnosis decision from doctors. Based on the background information of ECG signals, after analyzing some presented methods for ECG feature extraction, algorithm for each feature extraction have been proposed. The major methods for feature extraction we proposed contain short-time Fourier transform (STFT), Gabor filter, and matching process using Gaussian models with various scales. According to the experimental results, less comparative error shows that the proposed algorithm surpasses state-of-arts as stated in the literature for extracting features on ECG signals.

Original languageEnglish
Title of host publication2012 IEEE Biomedical Circuits and Systems Conference
Subtitle of host publicationIntelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications
Pages304-307
Number of pages4
DOIs
Publication statusPublished - 2012 Dec 1
Event2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Hsinchu, Taiwan
Duration: 2012 Nov 282012 Nov 30

Publication series

Name2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications

Other

Other2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012
CountryTaiwan
CityHsinchu
Period12-11-2812-11-30

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Biomedical Engineering

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