ECG features and methods for automatic classification of ventricular premature and ischemic heartbeats: A comprehensive experimental study

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081731%3A_____%2F17%3A00482149" target="_blank" >RIV/68081731:_____/17:00482149 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216305:26220/17:PU124688 RIV/00216224:14110/17:00097888

Výsledek na webu

<a href="http://www.nature.com/articles/s41598-017-10942-6" target="_blank" >http://www.nature.com/articles/s41598-017-10942-6</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41598-017-10942-6" target="_blank" >10.1038/s41598-017-10942-6</a>

Jazyk výsledku

angličtina

Název v původním jazyce

ECG features and methods for automatic classification of ventricular premature and ischemic heartbeats: A comprehensive experimental study

Popis výsledku v původním jazyce

Accurate detection of cardiac pathological events is an important part of electrocardiogram (ECG) evaluation and subsequent correct treatment of the patient. The paper introduces the results of a complex study, where various aspects of automatic classification of various heartbeat types have been addressed. Particularly, non-ischemic, ischemic (of two different grades) and subsequent ventricular premature beats were classified in this combination for the first time. ECGs recorded in rabbit isolated hearts under non-ischemic and ischemic conditions were used for analysis. Various morphological and spectral features (both commonly used and newly proposed) as well as classification models were tested on the same data set. It was found that: a) morphological features are generally more suitable than spectral ones, b) successful results (accuracy up to 98.3 percent and 96.2 percent for morphological and spectral features, respectively) can be achieved using features calculated without time-consuming delineation of QRS-T segment, c) use of reduced number of features (3 to 14 features) for model training allows achieving similar or even better performance as compared to the whole feature sets (10 to 29 features), d) k-nearest neighbours and support vector machine seem to be the most appropriate models (accuracy up to 98.6 percent and 93.5 percent, respectively).

Název v anglickém jazyce

ECG features and methods for automatic classification of ventricular premature and ischemic heartbeats: A comprehensive experimental study

Popis výsledku anglicky

Accurate detection of cardiac pathological events is an important part of electrocardiogram (ECG) evaluation and subsequent correct treatment of the patient. The paper introduces the results of a complex study, where various aspects of automatic classification of various heartbeat types have been addressed. Particularly, non-ischemic, ischemic (of two different grades) and subsequent ventricular premature beats were classified in this combination for the first time. ECGs recorded in rabbit isolated hearts under non-ischemic and ischemic conditions were used for analysis. Various morphological and spectral features (both commonly used and newly proposed) as well as classification models were tested on the same data set. It was found that: a) morphological features are generally more suitable than spectral ones, b) successful results (accuracy up to 98.3 percent and 96.2 percent for morphological and spectral features, respectively) can be achieved using features calculated without time-consuming delineation of QRS-T segment, c) use of reduced number of features (3 to 14 features) for model training allows achieving similar or even better performance as compared to the whole feature sets (10 to 29 features), d) k-nearest neighbours and support vector machine seem to be the most appropriate models (accuracy up to 98.6 percent and 93.5 percent, respectively).

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20601 - Medical engineering

Projekt

<a href="/cs/project/GAP102%2F12%2F2034" target="_blank" >GAP102/12/2034: Analýza vztahu mezi elektrickými ději a průtokem krve u srdečních komor</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název periodika

Scientific Reports

ISSN

2045-2322

e-ISSN

—

Svazek periodika

7

Číslo periodika v rámci svazku

SEP

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

11

Strana od-do

1-11

Kód UT WoS článku

000410064000075

EID výsledku v databázi Scopus

2-s2.0-85029325545