Robust Detection of R-Wave Using Wavelet Technique

Electrocardiogram (ECG) is considered to be the backbone of cardiology. ECG is composed of P, QRS & T waves and information related to cardiac diseases can be extracted from the intervals and amplitudes of these waves. The first step in extracting ECG features starts from the accurate detection of R peaks in the QRS complex. We have developed a robust R wave detector using wavelets. The wavelets used for detection are Daubechies and Symmetric. The method does not require any preprocessing therefore, only needs the ECG correct recordings while implementing the detection. The database has been collected from MIT-BIH arrhythmia database and the signals from Lead-II have been analyzed. MatLab 7.0 has been used to develop the algorithm. The ECG signal under test has been decomposed to the required level using the selected wavelet and the selection of detail coefficient d4 has been done based on energy, frequency and cross-correlation analysis of decomposition structure of ECG signal. The robustness of the method is apparent from the obtained results.

Authors:

• Awadhesh Pachauri
• Manabendra Bhuyan

Keywords:

• ECG
• P-QRS-T waves
• Wavelet Transform
• Hard Thresholding
• R-wave Detection.

References:

[1] Cuiwei Li, Chongxun Zheng, and Changfeng Tai, " Detection of
ECG Characteristic points using Wavelet Transforms",IEEE Trans.
Biomed. Eng, Vol. 42, No. 1, 1995
[2] S. Z. Mahmoodabadi, A .Ahmadian , M. D.Abolhasani, M. Eslami, J. H.
Bidgoli, "ECG Feature Extraction Based on Multiresolution Wavelet
Transform," Proceedings of the 2005 IEEE, Engineering in Medicine
and Biology 27th Annual Conference Shanghai, China, September 1-4,
2005.
[3] S.C. Saxena, V. Kumar and S.T. Hande, "QRS Detection using New
Wavelets", Journal of Medical Engineering & Technology, Volume 26,
November1, pages 7-15, (2002)
[4] Robi Polikar,"The Wavelet Tutorial Part IV, Multiresolution Analysis:
The Discrete Wavelet Transform",
www.cs.ucf.edu/courses/cap5015/WTpart4.pdf, (2008).
[5] Paul S addition, "Wavelet Transforms and the ECG: A Review,"
Institute of Physics Publishing, Physiol. Meas.26 (2005) R155-R199.
[6] C.S. Gargour and V. Ramachandran, "A Scheme for Teaching wavelets
at the introductory Level", Frontiers in Education Conference, 1997.
27th Annual Conference. 'Teaching and Learning in an Era of Change'.
Proceedings. Pittsburgh, PA, USA, 5-8 Nov 1997, http://fie.engrng.pitt.
edu/fie97/papers/1030.pdf
[7] J.S.Sahambi, S.N. Tandon, R.K.P. Bhatt, "Using Wavelet Transforms
for ECG Characterization, An Online Digital Signal Processing
System", IEEE Engineering In Medicine & Biology, Jan/Feb, 1997
[8] http://www.physionet.org/mitdb
[9] Wills J.Tompkins, Biomedical Digital Signal Processing, Prentice Hall
of India, New Delhi. 1993, ISBN: 0-13-67216-5
[10] Romero Legarreta, PS Addition, N Grubb, GR Clegg, CE Robertson,
KAA Fox, JN Watson, "R-Wave Detection Using Continuous Wavelet
Modulus Maxima", Computers in Cardiology 2003, 30, 565-568 ,0276-
6547/03, IEEE 2003.