Thursday 25th of April 2024
 

ECG Analysis based on Wavelet Transform and Modulus Maxima


Mourad Talbi, Akram Aouinet, Riadh Baazaoui and Adnane Cherif

In this paper, we have developed a new technique of P, Q, R, S and T Peaks detection using Wavelet Transform (WT) and Modulus maxima. One of the commonest problems in electrocardiogram (ECG) signal processing, is baseline wander removal suppression. Therefore we have removed the baseline wander in order to make easier the detection of the peaks P and T. Those peaks are detected after the QRS detection. The proposed method is based on the application of the discritized continuous wavelet transform (Mycwt) used for the Bionic wavelet transform, to the ECG signal in order to detect R-peaks in the first stage and in the second stage, the Q and S peaks are detected using the R-peaks localization. Finally the Modulus maxima are used in the undecimated wavelet transform (UDWT) domain in order to detect the others peaks (P, T). This detection is performed by using a varying-length window that is moving along the whole signal. For evaluating the proposed method, we have compared it to others techniques based on wavelets. In this evaluation, we have used many ECG signals taken from MIT-BIH database. The obtained results show that the proposed method outperforms a number of conventional techniques used for our evaluation.

Keywords: Baseline drift, Continuous Wavelet Transform, Electrocardiogram, Modulus maxima, Thresholds, Window analysis.

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ABOUT THE AUTHORS

Mourad Talbi
High School of Applied Mathematics and Informatics of Kairouan

Akram Aouinet
Faculty of sciences of Tunis

Riadh Baazaoui
Faculty of sciences of Tunis

Adnane Cherif
Faculty of sciences of Tunis


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