Sample Entropy Analysis of Noisy Atrial Electrograms during Atrial Fibrillation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F18%3A00323048" target="_blank" >RIV/68407700:21230/18:00323048 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21730/18:00323048
Result on the web
<a href="https://doi.org/10.1155/2018/1874651" target="_blank" >https://doi.org/10.1155/2018/1874651</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1155/2018/1874651" target="_blank" >10.1155/2018/1874651</a>
Alternative languages
Result language
angličtina
Original language name
Sample Entropy Analysis of Noisy Atrial Electrograms during Atrial Fibrillation
Original language description
Most cardiac arrhythmias can be classified as atrial flutter, focal atrial tachycardia, or atrial fibrillation. They have been usually treated using drugs, but catheter ablation has proven more effective. This is an invasive method devised to destroy the heart tissue that disturbs correct heart rhythm. In order to accurately localise the focus of this disturbance, the acquisition and processing of atrial electrograms form the usual mapping technique. They can be single potentials, double potentials, or complex fractionated atrial electrogram (CFAE) potentials, and last ones are the most effective targets for ablation. The electrophysiological substrate is then localised by a suitable signal processing method. Sample Entropy is a statistic scarcely applied to electrograms but can arguably become a powerful tool to analyse these time series, supported by its results in other similar biomedical applications. However, the lack of an analysis of its dependence on the perturbations usually found in electrogram data, such as missing samples or spikes, is even more marked. This paper applied SampEn to the segmentation between non-CFAE and CFAE records and assessed its class segmentation power loss at different levels of these perturbations. The results confirmed that SampEn was able to significantly distinguish between non-CFAE and CFAE records, even under very unfavourable conditions, such as 50% of missing data or 10% of spikes.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Research Center for Informatics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Computational and Mathematical Methods in Medicine
ISSN
1748-670X
e-ISSN
1748-6718
Volume of the periodical
2018
Issue of the periodical within the volume
June
Country of publishing house
GB - UNITED KINGDOM
Number of pages
8
Pages from-to
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UT code for WoS article
000436293700001
EID of the result in the Scopus database
2-s2.0-85049380497