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Authors: Jonathan Moeyersons 1 ; Griet Goovaerts 1 ; Suzy Huijghebaert 2 ; Bert Vandenberk 3 ; Rik Willems 3 and Sabine Van Huffel 1

Affiliations: 1 KU Leuven and imec, Belgium ; 2 KU Leuven, Belgium ; 3 KU Leuven and University Hospitals Leuven, Belgium

ISBN: 978-989-758-212-7

Keyword(s): T wave end detection, electrocardiogram (ECG)

Related Ontology Subjects/Areas/Topics: Applications and Services ; Biomedical Engineering ; Biomedical Signal Processing ; Cardiovascular Signals ; Computer Vision, Visualization and Computer Graphics ; Medical Image Detection, Acquisition, Analysis and Processing

Abstract: T wave end detection is essential for electrocardiogram (ECG) processing and analysis. Several methods have been proposed and tested, but an objective comparison is lacking. In this paper, four different (semi-)automated methods are compared with the manually annotated T wave ends of the PhysioNet QT database. The first method is a semi-automatic method, based on a template matching algorithm. The second method uses the tangent of the steepest point of the descending limb of the T wave. The third and fourth method perform a maximum area search of, respectively, a trapezium and the area under the curve. In order to evaluate the accuracy and repeatability of the proposed algorithms, the mean and standard deviation (sd) of the detection errors were computed. This was performed for leads I and II separately, after selection of the best annotated T wave end per beat and after selection of the best lead. We demonstrated that the trapezium method is the least repeatable of all methods tested (sd=29.7ms), whilst the integral method scores best in terms of accuracy (mean=2.2ms). These findings were strengthened by the analysis of the generated Bland-Altman plots, where the smallest bias was observed for the integral method (-1.89ms). (More)

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Paper citation in several formats:
Moeyersons, J.; Goovaerts, G.; Huijghebaert, S.; Vandenberk, B.; Willems, R. and Van Huffel, S. (2017). Automated T Wave End Detection Methods - Comparison of Four Different Methods for T Wave End Detection.In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2017) ISBN 978-989-758-212-7, pages 92-98. DOI: 10.5220/0006171700920098

@conference{biosignals17,
author={Jonathan Moeyersons. and Griet Goovaerts. and Suzy Huijghebaert. and Bert Vandenberk. and Rik Willems. and Sabine Van Huffel.},
title={Automated T Wave End Detection Methods - Comparison of Four Different Methods for T Wave End Detection},
booktitle={Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2017)},
year={2017},
pages={92-98},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006171700920098},
isbn={978-989-758-212-7},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2017)
TI - Automated T Wave End Detection Methods - Comparison of Four Different Methods for T Wave End Detection
SN - 978-989-758-212-7
AU - Moeyersons, J.
AU - Goovaerts, G.
AU - Huijghebaert, S.
AU - Vandenberk, B.
AU - Willems, R.
AU - Van Huffel, S.
PY - 2017
SP - 92
EP - 98
DO - 10.5220/0006171700920098

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