Automatic detection of P, QRS and T patterns in 12 leads ECG signal based on CWT

Abstract : In this paper, a new method based on the continuous wavelet transform is described in order to detectthe QRS, P and T waves. QRS, P and T waves may be distinguished from noise, baseline drift or irregularheartbeats. The algorithm, described in this paper, has been evaluated using the Computers in Cardiology(CinC) Challenge 2011 database and also applied on the MIT-BIH Arrhythmia database (MITDB). The datafrom the CinC Challenge 2011 are standard 12 ECG leads recordings with full diagnostic bandwidthcompared to the MITDB which only includes two leads for each ECG signal. Firstly, our algorithm isvalidated using fifty 12 leads ECG samples from the CinC collection. The samples have been chosen in the“acceptable records” list given by Physionet. The detection and the duration delineation of the QRS, P andT waves given by our method are compared to expert physician results. The algorithm shows a sensitivityequal to 0.9987 for the QRS complex, 0.9917 for the T wave and 0.9906 for the P wave. The accuracy andthe Youden index values show that the method is reliable for the QRS, T and P waves detection anddelineation. Secondly, our algorithm is applied to the MITDB in order to compare the detection of QRSwave to results of other some works in the literature.
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https://hal-univ-bourgogne.archives-ouvertes.fr/hal-01343875
Contributeur : Sabir Jacquir <>
Soumis le : dimanche 10 juillet 2016 - 22:13:26
Dernière modification le : vendredi 12 avril 2019 - 14:54:07

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  • HAL Id : hal-01343875, version 1

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Maxime Yochum, Charlotte Renaud, Sabir Jacquir. Automatic detection of P, QRS and T patterns in 12 leads ECG signal based on CWT. Biomedical Signal Processing and Control, Elsevier, 2016, 25, pp.46-52. ⟨hal-01343875⟩

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