Gabor feature extraction for electrocardiogram signals

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

doi:10.1109/BioCAS.2012.6418436

Gabor feature extraction for electrocardiogram signals

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

電機工程學系

研究成果: Conference contribution

3 引文斯高帕斯（Scopus）

摘要

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.

原文	English
主出版物標題	2012 IEEE Biomedical Circuits and Systems Conference
主出版物子標題	Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications
頁面	304-307
頁數	4
DOIs	https://doi.org/10.1109/BioCAS.2012.6418436
出版狀態	Published - 2012 12月 1
事件	2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Hsinchu, Taiwan 持續時間: 2012 11月 28 → 2012 11月 30

出版系列

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

Other

Other	2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012
國家/地區	Taiwan
城市	Hsinchu
期間	12-11-28 → 12-11-30

All Science Journal Classification (ASJC) codes

硬體和架構
生物醫學工程

存取文件

10.1109/BioCAS.2012.6418436

其它文件與鏈接

引用此

Lee, G. G., Hu, J. Y., Chen, C. F., & Lin, H. H. (2012). Gabor feature extraction for electrocardiogram signals. 於 2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications (頁 304-307). 文章 6418436 (2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications). https://doi.org/10.1109/BioCAS.2012.6418436

Lee, Gwo Giun ; Hu, Jhen Yue ; Chen, Chun Fu 等. / Gabor feature extraction for electrocardiogram signals. 2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications. 2012. 頁 304-307 (2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications).

@inproceedings{f562471d1fe7464aa77a2517b420eefc,

title = "Gabor feature extraction for electrocardiogram signals",

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.",

author = "Lee, {Gwo Giun} and Hu, {Jhen Yue} and Chen, {Chun Fu} and Lin, {Huan Hsiang}",

year = "2012",

month = dec,

day = "1",

doi = "10.1109/BioCAS.2012.6418436",

language = "English",

isbn = "9781467322935",

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

pages = "304--307",

booktitle = "2012 IEEE Biomedical Circuits and Systems Conference",

note = "2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 ; Conference date: 28-11-2012 Through 30-11-2012",

}

Lee, GG, Hu, JY, Chen, CF & Lin, HH 2012, Gabor feature extraction for electrocardiogram signals. 於 2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications., 6418436, 2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications, 頁 304-307, 2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012, Hsinchu, Taiwan, 12-11-28. https://doi.org/10.1109/BioCAS.2012.6418436

Gabor feature extraction for electrocardiogram signals. / Lee, Gwo Giun; Hu, Jhen Yue; Chen, Chun Fu 等.
2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications. 2012. p. 304-307 6418436 (2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications).

研究成果: Conference contribution

TY - GEN

T1 - Gabor feature extraction for electrocardiogram signals

AU - Lee, Gwo Giun

AU - Hu, Jhen Yue

AU - Chen, Chun Fu

AU - Lin, Huan Hsiang

PY - 2012/12/1

Y1 - 2012/12/1

N2 - 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.

AB - 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.

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DO - 10.1109/BioCAS.2012.6418436

M3 - Conference contribution

AN - SCOPUS:84874178482

SN - 9781467322935

T3 - 2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications

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BT - 2012 IEEE Biomedical Circuits and Systems Conference

T2 - 2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012

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Lee GG, Hu JY, Chen CF, Lin HH. Gabor feature extraction for electrocardiogram signals. 於 2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications. 2012. p. 304-307. 6418436. (2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications). doi: 10.1109/BioCAS.2012.6418436

Gabor feature extraction for electrocardiogram signals

摘要

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Other

All Science Journal Classification (ASJC) codes

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