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2019 | OriginalPaper | Buchkapitel

Automatic Detection of P Wave in ECG During Ventricular Extrasystoles

verfasst von : Lucie Maršánová, Andrea Němcová, Radovan Smíšek, Tomáš Goldmann, Martin Vítek, Lukáš Smital

Erschienen in: World Congress on Medical Physics and Biomedical Engineering 2018

Verlag: Springer Singapore

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Abstract

This work introduces a new method for P wave detection in ECG signals during ventricular extrasystoles. The authors of previous works which deal with detection of P waves tested their algorithms mainly on physiological records (sinus rhythm) and they reached good results for these records. Testing of P wave detection algorithms using pathological records is usually not provided and if it is, the results are notably worse than in the case of physiological records. The automatic and reliable detection of atrial activity in pathological situations is still an unsolved problem. In this work, phasor transform in combination with classification algorithm is used for P wave detection. Phasor transform converts each ECG sample into a phasor which enhances changes in the ECG signal. The classification is based on extraction of morphological features which are derived from each QRS complex. The results of classification are used for demarcation of areas in which P waves are searched using phasor transform. The proposed algorithm was tested on signals no. 106, 119, 214 and 223 from MIT-BIH arrhythmia database, in which the ventricular extrasystoles are present. For validation whether the algorithm is functional also for signals with physiological rhythm, it was tested on the signals no. 100, 101, 103, 117, and 122. The accuracy of the P wave detection in signals with ventricular extrasystoles is Se = 98.94% and PP = 98.30% and in signals without pathology is Se = 98.47% and PP = 99.99%.

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Metadaten
Titel
Automatic Detection of P Wave in ECG During Ventricular Extrasystoles
verfasst von
Lucie Maršánová
Andrea Němcová
Radovan Smíšek
Tomáš Goldmann
Martin Vítek
Lukáš Smital
Copyright-Jahr
2019
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-9038-7_72

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