Detail publikace

Optimization of wavelet transform in the task of intracardiac ECG segmentation

ŘEDINA, R.

Originální název

Optimization of wavelet transform in the task of intracardiac ECG segmentation

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

My work deals with the selection of an appropriate wavelet transform setting for feature extraction from intracardiac ECG recordings. The studied signals were obtained during electrophysiological examinations at the Department of Pediatric Medicine, University Hospital Brno. In this paper, several wavelets are tested for feature extraction which is followed by adaptive thresholding to detect atrial activity from the extracted features. The procedure is evaluated using the F-score. Although the presented procedure does not appear to be overall effective for intracardiac signal segmentation, it certainly does not reject the use of wavelet transforms in combination with advanced machine learning, neural network, or deep learning techniques.

Klíčová slova

ECG; Intracardiac ECG; Atrial activity; Wavelet transform; Adaptive threshold; F-score

Autoři

ŘEDINA, R.

Vydáno

26. 4. 2022

Nakladatel

Brno University of Technology, Faculty of Electrical Engineering and Communication

Místo

Brno

ISBN

978-80-214-6029-4

Kniha

Proceedings I of the 28th Conference STUDENT EEICT 2022

Edice

1

Strany od

437

Strany do

441

Strany počet

5

URL

https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2022_sbornik_1.pdf

BibTex

@inproceedings{BUT178057,
  author="Richard {Ředina}",
  title="Optimization of wavelet transform in the task of intracardiac ECG segmentation",
  booktitle="Proceedings I of the 28th Conference STUDENT EEICT 2022",
  year="2022",
  series="1",
  pages="437--441",
  publisher="Brno University of Technology, Faculty of Electrical Engineering and Communication",
  address="Brno",
  isbn="978-80-214-6029-4",
  url="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2022_sbornik_1.pdf"
}