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R Peak Detection using Wavelet

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Amana Yadav, Naresh Grover
10.5120/ijca2017914635

Amana Yadav and Naresh Grover. R Peak Detection using Wavelet. International Journal of Computer Applications 169(3):40-43, July 2017. BibTeX

@article{10.5120/ijca2017914635,
	author = {Amana Yadav and Naresh Grover},
	title = {R Peak Detection using Wavelet},
	journal = {International Journal of Computer Applications},
	issue_date = {July 2017},
	volume = {169},
	number = {3},
	month = {Jul},
	year = {2017},
	issn = {0975-8887},
	pages = {40-43},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume169/number3/27969-2017914635},
	doi = {10.5120/ijca2017914635},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

ECG is very crucial and important tool to detect the cardiac problems. It has all the information related to the electrical activities of heart. This also has the information of normal and abnormal activities for the detection of the diseases. So it is essential and important to detect the accurate R-peaks in QRS complex, especially when the results are to be used for clinical applications. Hence in a long-term ECG signal, automatic R-peaks detection is very essential to diagnose cardiac disorders. In this paper we proposed a robust technique to detect R-peak which uses Wavelet Transform. The proposed R Peak detector is consists of a wavelet filter banks, a noise detector with zero-crossing points, multi-scaled product algorithm and soft-threshold algorithm.

References

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Keywords

ECG, R-peak detection, QRS complex, P-QRS-T waves, Filters, MATLAB.