A NEW real-time ECG R-wave detection algorithm

A new real-time detection algorithm, which combines merits of the real-time detection algorithm proposed by Pan and the QRS detection algorithm based on Hilbert transform, is proposed to improve detection accuracy of ECG R-wave. The original data are firstly processed by using of Hilbert transform to improve the signal to noise ratio (SNR). Considering the quasi-periodic characteristics of the ECG, the adaptive threshold designed in Pan's real-time detection algorithm is adopted to execute threshold detection for ECG waveform with small range. In this paper, the MIT/BIH Arrhythmia Database are used to verify the effectiveness of the proposed algorithm, and the results show an average R-wave detection error rate of 0.63%. Comparing with results obtained in other literatures, implementation of the algorithm is significantly simplified while the detection accuracy is favorable.

[1]  Willis J. Tompkins,et al.  A Real-Time QRS Detection Algorithm , 1985, IEEE Transactions on Biomedical Engineering.

[2]  A. Charef,et al.  Digital fractional order operators for R-wave detection in electrocardiogram signal , 2009 .

[3]  Szi-Wen Chen,et al.  A real-time QRS detection method based on moving-averaging incorporating with wavelet denoising , 2006, Comput. Methods Programs Biomed..

[4]  D.S. Benitez,et al.  A new QRS detection algorithm based on the Hilbert transform , 2000, Computers in Cardiology 2000. Vol.27 (Cat. 00CH37163).

[5]  A. Schuck,et al.  QRS detector pre-processing using the complex wavelet transform , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

[6]  Liang-Yu Shyu,et al.  Using wavelet transform and fuzzy neural network for VPC detection from the holter ECG , 2004, IEEE Transactions on Biomedical Engineering.

[7]  H. T. Nagle,et al.  A comparison of the noise sensitivity of nine QRS detection algorithms , 1990, IEEE Transactions on Biomedical Engineering.