Advanced P Wave Detection in Ecg Signals During Pathology: Evaluation in Different Arrhythmia Contexts
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081731%3A_____%2F19%3A00524970" target="_blank" >RIV/68081731:_____/19:00524970 - isvavai.cz</a>
Alternative codes found
RIV/00216305:26220/19:PU134327
Result on the web
<a href="https://www.nature.com/articles/s41598-019-55323-3.pdf" target="_blank" >https://www.nature.com/articles/s41598-019-55323-3.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1038/s41598-019-55323-3" target="_blank" >10.1038/s41598-019-55323-3</a>
Alternative languages
Result language
angličtina
Original language name
Advanced P Wave Detection in Ecg Signals During Pathology: Evaluation in Different Arrhythmia Contexts
Original language description
Reliable P wave detection is necessary for accurate and automatic electrocardiogram (ECG) analysis. Currently, methods for P wave detection in physiological conditions are well-described and efficient. However, methods for P wave detection during pathology are not generally found in the literature, or their performance is insufficient. This work introduces a novel method, based on a phasor transform, as well as innovative rules that improve P wave detection during pathology. These rules are based on the extraction of a heartbeats' morphological features and knowledge of heart manifestation during both physiological and pathological conditions. To properly evaluate the performance of the proposed algorithm in pathological conditions, a standard database with a sufficient number of reference P wave positions is needed. However, such a database did not exist. Thus, ECG experts annotated 12 chosen pathological records from the MIT-BIH Arrhythmia Database. These annotations are publicly available via Physionet. The algorithm performance was also validated using physiological records from the MIT-BIH Arrhythmia and QT databases. The results for physiological signals were Se =98.42% and PP =99.98%, which is comparable to other methods. For pathological signals, the proposed method reached Se = 96.40% and PP = 85.84%, which greatly outperforms other methods. This improvement represents a huge step towards fully automated analysis systems being respected by ECG experts. These systems are necessary, particularly in the area of long-term monitoring.
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
30201 - Cardiac and Cardiovascular systems
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Scientific Reports
ISSN
2045-2322
e-ISSN
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Volume of the periodical
9
Issue of the periodical within the volume
DEC
Country of publishing house
GB - UNITED KINGDOM
Number of pages
11
Pages from-to
19053
UT code for WoS article
000503162500001
EID of the result in the Scopus database
2-s2.0-85076549579