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