Automatic Detection of the Wolff-Parkinson-White Syndrome from Electrocardiograms
| Affiliation auteurs | !!!! Error affiliation !!!! |
| Titre | Automatic Detection of the Wolff-Parkinson-White Syndrome from Electrocardiograms |
| Type de publication | Conference Paper |
| Year of Publication | 2016 |
| Auteurs | Mahamat HAdam, Jacquir S, Khalil C, Laurent G, Binczak S |
| Editor | Murray A |
| Conference Name | 2016 COMPUTING IN CARDIOLOGY CONFERENCE (CINC), VOL 43 |
| Publisher | IEEE |
| Conference Location | 345 E 47TH ST, NEW YORK, NY 10017 USA |
| ISBN Number | 978-1-5090-0895-7 |
| Résumé | In this paper, a new method of automatic detection of the Wolff-Parkinson-White (WPW) syndrome is proposed based on electrocardiograms (ECGs) signals. Firstly, with the continuous wavelet transform (CWT), the P wave, the T wave and the QRS complex are identified. Then, their durations are also computed after determination of the boundaries (onsets and offsets of the P, T waves and the QRS complex). Secondly, the PR interval, the QRS complex interval and the area of the QRS complex are determined in order to detect the presence or not of the delta wave. This method has been tested on ECGs signals from patients affected by the WPW syndrome in order to evaluate its robustness. It can provide assistance to cardiologists during the interpretation of the ECG. |