Advanced R Wave Detection Algorithm Using Wavelet and Adaptive Threshold 


Vol. 35,  No. 10, pp. 840-846, Oct.  2010


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  Abstract

The Holter electrocardiogram is used in the diagnosis of a arrhythmia after attaching to body for tewnty-four hours or more. But it is difficult to analyze the ECG signal because of various noise types. In Holter electrocardiogram, the most important problem in recording ECG signal is a baseline wandering, which is occurred by rhythm of respiration and muscle contraction attaching to an electrode. Therefore, advanced R wave detection method using wavelet and adaptive threshold is presented in this paper. For this purpose, we removed baseline wandering of low frequency band and made a summed signals that are composed of two high frequency bands including frequency component of QRS complex using the wavelet filter. And then we designed R wave detection algorithm using the adaptive threshold and window through RR interval. For evaluation of the suggested R wave detection Algorithm, we compared our algorithm with existing algorithms using the MIT-BIH database. Our algorithm showed the accuracy of 99.76% and the higher performance of R wave detection than existing algorithms.

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  Cite this article

[IEEE Style]

I. Cho and H. Kwon, "Advanced R Wave Detection Algorithm Using Wavelet and Adaptive Threshold," The Journal of Korean Institute of Communications and Information Sciences, vol. 35, no. 10, pp. 840-846, 2010. DOI: .

[ACM Style]

Ik-Sung Cho and Hyeog-Soong Kwon. 2010. Advanced R Wave Detection Algorithm Using Wavelet and Adaptive Threshold. The Journal of Korean Institute of Communications and Information Sciences, 35, 10, (2010), 840-846. DOI: .

[KICS Style]

Ik-Sung Cho and Hyeog-Soong Kwon, "Advanced R Wave Detection Algorithm Using Wavelet and Adaptive Threshold," The Journal of Korean Institute of Communications and Information Sciences, vol. 35, no. 10, pp. 840-846, 10. 2010.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880