Wolff-Parkinson-White (WPW) syndrome: The detection of delta wave in an electrocardiogram (ECG)
| Autor: | Sabir Jacquir, Cliff Khalil, Hassan Adam Mahamat, Stéphane Binczak, Gabriel Laurent |
|---|---|
| Přispěvatelé: | Université de Bourgogne (UB), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Delta
Male medicine.medical_specialty Databases Factual Speech recognition [SDV]Life Sciences [q-bio] 0206 medical engineering Wavelet Analysis 02 engineering and technology 03 medical and health sciences QRS complex Electrocardiography [SPI]Engineering Sciences [physics] 0302 clinical medicine Wavelet T wave Internal medicine medicine Humans cardiovascular diseases Continuous wavelet transform ComputingMilieux_MISCELLANEOUS medicine.diagnostic_test business.industry Wolff-Parkinson-White (WPW) syndrome Signal Processing Computer-Assisted Middle Aged medicine.disease 020601 biomedical engineering WPW SYNDROME Cardiology Female Wolff-Parkinson-White Syndrome business 030217 neurology & neurosurgery Algorithms |
| Zdroj: | 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Aug 2016, Orlando, France. pp.3809-3812, ⟨10.1109/EMBC.2016.7591558⟩ EMBC |
| Popis: | The delta wave remains an important indicator to diagnose the WPW syndrome. In this paper, a new method of detection of delta wave in an ECG signal is proposed. Firstly, using the continuous wavelet transform, the P wave, the QRS complex and the T wave are detected, then their durations are computed after determination of the boundary location (onsets and offsets of the P, QRS and T waves). Secondly, the PR duration, the QRS duration and the upstroke of the QRS complex are used to determine the presence or absence of the delta wave. This algorithm has been tested on the Physionel database (ptbdb) in order to evaluate its robustness. It has been applied to clinical signals from patients affected by WPW syndrome. This method can provide assistance to practitioners in order to detect the WPW syndrome. |
| Databáze: | OpenAIRE |
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