Call for Paper - March 2020 Edition
IJCA solicits original research papers for the March 2020 Edition. Last date of manuscript submission is February 20, 2020. Read More

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

Print
PDF
CASCT
© 2010 by IJCA Journal
Number 1 - Article 2
Year of Publication: 2010
Authors:
Nopadol Uchaipichat
Sakonthawat Inban
10.5120/998-32

Nopadol Uchaipichat Sakonthawat Inban. Article: Development of QRS Detection using Short-time Fourier Transform based Technique. IJCA,Special Issue on CASCT (1):7–10, 2010. Published By Foundation of Computer Science. BibTeX

@article{key:article,
	author = {Sakonthawat Inban, Nopadol Uchaipichat},
	title = {Article: Development of QRS Detection using Short-time Fourier Transform based Technique},
	journal = {IJCA,Special Issue on CASCT},
	year = {2010},
	number = {1},
	pages = {7--10},
	note = {Published By Foundation of Computer Science}
}

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%.

Reference

  • Houghton, A.R. and Gray, D., 1997, Making Sense of the ECG, A hands-on guide, ARNOLD.
  • Chen, S.-W., Chen, H.-C., Chan, H.-L., 2006, A real-time QRS detection method based on moving-averaging incorporating with wavelet denoising, Computer Methods and Programs in Biomedicine, 82 (2006), 187-195.
  • Darrington, J., 2006, Towards real time QRS detection: A fast method using minimal pre-processing, Biomedical Signal Processing and Control, 1 (2006), 169-176.
  • Mehta, S.S., Shete, D.A., Lingayat, N.S., Chouhan, V.S., 2010, IRBM, 31 (2010), 48-54.
  • Mehta, S.S., Lingayat, N.S., 2008, SVM-based algorithm for recognition of QRS complexes in electrocardiogram, IRBM, 29 (2008), 310-317.
  • Goldberger, A.L., Amaral, L.A.N., Glass, L., Hausdorff, J.M., Ivanov, P.Ch., Mark, R.G., Mietus, J.E., Moody, G.B., Peng, C-K., Stanley, H.E., 2000, PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals, Circulation, 101 (2000), E215-220.
  • Gade, S., Gram-Hansen, K., 1997, The analysis of nonstationary signals, Sound and Vibration, 31(1997), 40-46.
  • Rioul, O., Vetterli, M., 1991, Wavelets and signal processing , IEEE Signal Processing Magazine, 8 (1991) 14-38.