JSIP  Vol.6 No.3 , August 2015
P-Wave Detection Combining Entropic Criterion and Wavelet Transform
Abstract: The objective of this paper is to develop an efficient P wave detection method in electrocardiogram (ECG) using the local entropy criterion (EC) and wavelet transform (WT) modulus maxima. The detection of P wave relates to the diagnosis of many heart diseases and it is also a difficult point during the ECG signal detection. Determining the position of a P-wave is complicated due to the low amplitude, the ambiguous and changing form of the complex. In a first step, QRS complexes are detected using the pan-Tompkins method. Then, we look for the best position of the analysis window and the value of the most appropriate width to the P wave. Finally, the determination of P wave peaks, as well as their onsets and offsets. The method has been validated using ECG-recordings with a wide variety of P-wave morphologies from MIT-BIH Arrhythmia and QT database. The P-wave method obtains a sensitivity of 99.87% and a positive predictivity of 98.04% over the MIT-BIH Arrhythmia, while for the QT, sensitivity and predictivity over 99.8% are attained.
Cite this paper: Rekik, S. and Ellouze, N. (2015) P-Wave Detection Combining Entropic Criterion and Wavelet Transform. Journal of Signal and Information Processing, 6, 217-226. doi: 10.4236/jsip.2015.63020.

[1]   Le Page, R. and Boucher, J. (2001) Détection et Analyse de l’Onde P d’Un Electrocardiogramme. Colloque GRETSI’01, France.

[2]   Li, C., Zheng, C. and Tai, C. (1995) Detection of ECG Characteristic Points Using Wavelet Transform. IEEE Transactions on Biomedical Engineering, 42, 21-28.

[3]   Mallat, S. and Hwang, W.L. (1992) Singularity Detection and Processing with Wavelets. IEEE Transactions on Information Theory, 38, 617-643.

[4]   Djafari, M. (1998) Entropy in Signal Processing. Laboratory of Signal and System CNRS-SUPELEC-UPS, 15, 541-551.

[5]   Mallat, S. (1991) Zero-Crossings of a Wavelet Transform. IEEE Transactions on Information Theory, 37, 1019-1033.

[6]   Clavier, L. (1997) Analyse du signal électrocardiographique en vue du dépistage de la fibrillation auriculaire. Thèse de l’Université de Rennes I.

[7]   McNames, J. (2005) Optimal Rate Filters for Biomedical Point Processes. 27th Annual International Conference of the Engineering in Medicine and Biology Society, Shanghai, 17-18 January 2006, 145-148.

[8]   Belgacem, N., Chikh, M. and Reguig, F. (2003) Détection et Identification des Arythmies Cardiaques Par Application des Réseaux de Neurones. Conférence Internationale sur les Systèmes de Télécommunications d’Electronique Médicale et d’Automatique CISTEMA, Tlemcen, 27-29 September 2003, 236-239.

[9]   Khelil, B., Kachouri, A. and Ben Messaoud, M. (2006) Nouvelle Tendance Technologiques en Génie Electrique et Informatique. Springer, New York.

[10]   Pan, J. and Tompkins, W. (1985) A Real Time QRS Detection Algorithm. IEEE Transactions on Biomedical Engineering, 32, 230-236.

[11]   Shannon, C. and Weaver, W. (1948) The Mathematical Theory of Communication. Bell System Technical Journal, 27, 379-423, 623-656.

[12]   Mallat, S. and Zhong, S. (1992) Characterization of Signals from Multiscale Edge. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14, 710-732.

[13]   Moody, G.B. and Mark, R.G. (2001) The Impact of the MIT-BIH Arrhythmia Database. IEEE Engineering in Medicine and Biology Magazine, 20, 45-50.

[14]   QT ECG Database (1997) Massachusetts Institute of Technology.

[15]   Almeida, R., Martinez, J.P., Olmos, S., Rocha, A.P. and Laguna, P. (2004) A Wavelet-Based ECG Delineator: Evaluation on Standard Databases. IEEE Transactions on Biomedical Engineering, 51, 570-581.