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Evaluating Pauses in Holter ECG Signals

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F22%3APU142247" target="_blank" >RIV/00216305:26220/22:PU142247 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://www.cinc.org/2021/Program/accepted/107_Preprint.pdf" target="_blank" >https://www.cinc.org/2021/Program/accepted/107_Preprint.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.23919/CinC53138.2021.9662914" target="_blank" >10.23919/CinC53138.2021.9662914</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Evaluating Pauses in Holter ECG Signals

  • Popis výsledku v původním jazyce

    Background: Information related to pauses in heart activity is an important output of ECG Holter monitoring reports. This information should be quickly assessed from inter-beat (RR) intervals only (a naïve approach). However, evaluating pauses in Holter ECGs recorded during usual daily activities can be more challenging due to signal lower quality. In this paper, we propose a method to improve pause detection in heart activity from Holter ECG recordings. Method: We used 978 recordings (length 45 seconds, 1-lead ECG, sampled at 200 or 250 Hz) with a known longest RR interval (from 1.12 to 19.0 seconds, mean duration of 2.72 ± 1.26 seconds). QRS complexes were detected by a convolutional neural network with a recurrent layer. This study started with the automated removal of suspicious QRS complexes by a QRS amplitude. Then we iterated through RR intervals, seeking saturated areas, missed QRS, or a strong noise; potentially, examined RR intervals were further refined. The longest interval was reported for each recording. Results: A mean difference between computed and expert values was 0.079 ± 0.433 and 0.046 ± 0.120 seconds for the naïve and the proposed approach, respectively. The ability to find severe pauses (equal to or longer than 4 seconds) showed an F1 score of 0.95 and 0.97 for naïve and the proposed method. Conclusion: Our results showed that the proposed method improved pause detection in Holter ECG recordings compared to the naïve approach.

  • Název v anglickém jazyce

    Evaluating Pauses in Holter ECG Signals

  • Popis výsledku anglicky

    Background: Information related to pauses in heart activity is an important output of ECG Holter monitoring reports. This information should be quickly assessed from inter-beat (RR) intervals only (a naïve approach). However, evaluating pauses in Holter ECGs recorded during usual daily activities can be more challenging due to signal lower quality. In this paper, we propose a method to improve pause detection in heart activity from Holter ECG recordings. Method: We used 978 recordings (length 45 seconds, 1-lead ECG, sampled at 200 or 250 Hz) with a known longest RR interval (from 1.12 to 19.0 seconds, mean duration of 2.72 ± 1.26 seconds). QRS complexes were detected by a convolutional neural network with a recurrent layer. This study started with the automated removal of suspicious QRS complexes by a QRS amplitude. Then we iterated through RR intervals, seeking saturated areas, missed QRS, or a strong noise; potentially, examined RR intervals were further refined. The longest interval was reported for each recording. Results: A mean difference between computed and expert values was 0.079 ± 0.433 and 0.046 ± 0.120 seconds for the naïve and the proposed approach, respectively. The ability to find severe pauses (equal to or longer than 4 seconds) showed an F1 score of 0.95 and 0.97 for naïve and the proposed method. Conclusion: Our results showed that the proposed method improved pause detection in Holter ECG recordings compared to the naïve approach.

Klasifikace

  • Druh

    D - Stať ve sborníku

  • CEP obor

  • OECD FORD obor

    20601 - Medical engineering

Návaznosti výsledku

  • Projekt

  • Návaznosti

    S - Specificky vyzkum na vysokych skolach

Ostatní

  • Rok uplatnění

    2022

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název statě ve sborníku

    Computing in Cardiology 2021

  • ISBN

  • ISSN

    2325-887X

  • e-ISSN

  • Počet stran výsledku

    4

  • Strana od-do

    1-4

  • Název nakladatele

    IEEE

  • Místo vydání

    Brno, Czech republic

  • Místo konání akce

    Brno

  • Datum konání akce

    12. 9. 2021

  • Typ akce podle státní příslušnosti

    WRD - Celosvětová akce

  • Kód UT WoS článku

    000821955000202