Automatic Detection of Strict Left Bundle Branch Block

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F18%3APU127907" target="_blank" >RIV/00216305:26220/18:PU127907 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00159816:_____/19:00072534

Výsledek na webu

<a href="https://www.springer.com/us/book/9789811090226#aboutBook" target="_blank" >https://www.springer.com/us/book/9789811090226#aboutBook</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-981-10-9038-7_82" target="_blank" >10.1007/978-981-10-9038-7_82</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Automatic Detection of Strict Left Bundle Branch Block

Popis výsledku v původním jazyce

Strict (true) left bundle branch block (tLBBB) ECG morphology is a new diagnostic marker in cardiology that was proposed to predict cardiac resynchronization therapy (CRT) responders. In this paper we present an algorithm for the automatic detection of tLBBB. This algorithm includes mid-QRS notching and slurring detection, QRS duration measurement and tLBBB morphology detection. All required morphologies are detected in the time domain using thresholding of simple features of signal. In order to test our algorithms, three experts labelled 78 ECG records (12 leads, fs = 5 kHz, 15 min); 51 records were labeled as tLBBB. The proposed algorithms were tested showing overall sensitivity and specificity 98 and 86%, respectively, in cases where all three experts reached full consensus (82% of the dataset). Our method showed lower sensitivity and higher specificity 96% and 88%, respectively, for the dataset including cases where experts mutually disagreed, consensus has been reached through expert discussion in these records.

Název v anglickém jazyce

Automatic Detection of Strict Left Bundle Branch Block

Popis výsledku anglicky

Strict (true) left bundle branch block (tLBBB) ECG morphology is a new diagnostic marker in cardiology that was proposed to predict cardiac resynchronization therapy (CRT) responders. In this paper we present an algorithm for the automatic detection of tLBBB. This algorithm includes mid-QRS notching and slurring detection, QRS duration measurement and tLBBB morphology detection. All required morphologies are detected in the time domain using thresholding of simple features of signal. In order to test our algorithms, three experts labelled 78 ECG records (12 leads, fs = 5 kHz, 15 min); 51 records were labeled as tLBBB. The proposed algorithms were tested showing overall sensitivity and specificity 98 and 86%, respectively, in cases where all three experts reached full consensus (82% of the dataset). Our method showed lower sensitivity and higher specificity 96% and 88%, respectively, for the dataset including cases where experts mutually disagreed, consensus has been reached through expert discussion in these records.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20601 - Medical engineering

Projekt

<a href="/cs/project/GA17-13830S" target="_blank" >GA17-13830S: Analytické metody pro pokročilou identifikaci komorové dyssynchronie</a><br>

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název statě ve sborníku

World Congress on Medical Physics and Biomedical Engineering 2018

ISBN

978-981-10-9038-7

ISSN

1680-0737

e-ISSN

—

Počet stran výsledku

5

Strana od-do

1-5

Název nakladatele

Springer Singapore

Místo vydání

Prague, Czech Republic

Místo konání akce

Prague

Datum konání akce

3. 6. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000449742700082