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Reseach Article

Development of QRS Detection using Short-time Fourier Transform based Technique

Published on None 2010 by Sakonthawat Inban, Nopadol Uchaipichat
Computer Aided Soft Computing Techniques for Imaging and Biomedical Applications
Foundation of Computer Science USA
CASCT - Number 1
None 2010
Authors: Sakonthawat Inban, Nopadol Uchaipichat
13efffd6-79f4-4df5-94fc-6a2de9344136

Sakonthawat Inban, Nopadol Uchaipichat . Development of QRS Detection using Short-time Fourier Transform based Technique. Computer Aided Soft Computing Techniques for Imaging and Biomedical Applications. CASCT, 1 (None 2010), 7-10.

@article{
author = { Sakonthawat Inban, Nopadol Uchaipichat },
title = { Development of QRS Detection using Short-time Fourier Transform based Technique },
journal = { Computer Aided Soft Computing Techniques for Imaging and Biomedical Applications },
issue_date = { None 2010 },
volume = { CASCT },
number = { 1 },
month = { None },
year = { 2010 },
issn = 0975-8887,
pages = { 7-10 },
numpages = 4,
url = { /specialissues/casct/number1/998-32/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 Computer Aided Soft Computing Techniques for Imaging and Biomedical Applications
%A Sakonthawat Inban
%A Nopadol Uchaipichat
%T Development of QRS Detection using Short-time Fourier Transform based Technique
%J Computer Aided Soft Computing Techniques for Imaging and Biomedical Applications
%@ 0975-8887
%V CASCT
%N 1
%P 7-10
%D 2010
%I International Journal of Computer Applications
Abstract

This paper reports our study in QRS complex detection. The short-time Fourier transform (STFT) was employed in ECG filtering stage. The narrow rectangular window was used to transform ECG signals into time-frequency domain. The temporal information at 45 Hz from spectrogram was analyzed for detecting QRS locations. The automated thresholding combined with local maxima finding method was modified to find the QRS location. The data used in this study is MIT-BIH Arrhythmia database. As the results, our proposed technique achieved the detection rate better than 99% and fail ratio was 1.3%.

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Index Terms

Computer Science
Information Sciences

Keywords

QRS detection Electrocardiogram Shot-time Fourier Transform