Advanced P Wave Detection in Ecg Signals During Pathology: Evaluation in Different Arrhythmia Contexts
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU134327" target="_blank" >RIV/00216305:26220/19:PU134327 - isvavai.cz</a>
Nalezeny alternativní kódy
RIV/68081731:_____/19:00524970
Výsledek na webu
<a href="https://www.nature.com/articles/s41598-019-55323-3" target="_blank" >https://www.nature.com/articles/s41598-019-55323-3</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>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Advanced P Wave Detection in Ecg Signals During Pathology: Evaluation in Different Arrhythmia Contexts
Popis výsledku v původním jazyce
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.
Název v anglickém jazyce
Advanced P Wave Detection in Ecg Signals During Pathology: Evaluation in Different Arrhythmia Contexts
Popis výsledku anglicky
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.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10700 - Other natural sciences
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2019
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Scientific Reports
ISSN
2045-2322
e-ISSN
—
Svazek periodika
9
Číslo periodika v rámci svazku
18582
Stát vydavatele periodika
GB - Spojené království Velké Británie a Severního Irska
Počet stran výsledku
11
Strana od-do
1-11
Kód UT WoS článku
000503162500001
EID výsledku v databázi Scopus
2-s2.0-85076549579