Publication detail

Optimization of wavelet transform in the task of intracardiac ECG segmentation

ŘEDINA, R.

Original Title

Optimization of wavelet transform in the task of intracardiac ECG segmentation

Type

conference paper

Language

English

Original Abstract

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.

Keywords

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

Authors

ŘEDINA, R.

Released

26. 4. 2022

Publisher

Brno University of Technology, Faculty of Electrical Engineering and Communication

Location

Brno

ISBN

978-80-214-6029-4

Book

Proceedings I of the 28th Conference STUDENT EEICT 2022

Edition

1

Pages from

437

Pages to

441

Pages count

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"
}