Feature subset selection and classification of intracardiac electrograms during atrial fibrillation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00312281" target="_blank" >RIV/68407700:21230/17:00312281 - isvavai.cz</a>

Alternative codes found

RIV/68407700:21730/17:00312281

Result on the web

<a href="http://www.sciencedirect.com/science/article/pii/S1746809417301088" target="_blank" >http://www.sciencedirect.com/science/article/pii/S1746809417301088</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.bspc.2017.06.005" target="_blank" >10.1016/j.bspc.2017.06.005</a>

Result language

angličtina

Original language name

Feature subset selection and classification of intracardiac electrograms during atrial fibrillation

Original language description

Several approaches have been adopted for the identification of arrhythmogenic sources maintaining atrial fibrillation (AF). In this paper, we propose a classifier that discriminates between four classes of atrial electrogram (EGM). We delved into the relation between levels of fractionation in EGM signals and the fibrillation substrates in simulated episodes of chronic AF. Several feature extraction methods were used to calculate 92 features from 429 real EGM records acquired during radiofrequency ablation of chronic AF. We selected the optimal subset of features by using a genetic algorithm, followed by K-nearest neighbors (K-NN) classification into four levels of fractionation. Sensitivity of 0.90 and specificity of 0.97 were achieved. Subsequently, the results of the classification were extrapolated to signals of a 3D human atria model and a 2D model of atrial tissue. The 3D model simulated an episode of AF maintained by a rotor in the posterior wall of the left atrium and the 2D model simulated an AF episode with one stable rotor. We used the K-NN classifier trained on a given set of real EGM signals to detect a specific class of signals presenting the highest level of fractionation located near the rotor's vortex. This method needs to be tested on real clinical data to provide evidence that it can support ablation therapy procedures.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GPP103%2F11%2FP106" target="_blank" >GPP103/11/P106: Integration of digital signal processing and artificial intelligence methods for intracardial signal complexity evaluation</a><br>

Continuities

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

Publication year

2017

Confidentiality

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

Name of the periodical

Biomedical Signal Processing and Control

ISSN

1746-8094

e-ISSN

1746-8108

Volume of the periodical

38

Issue of the periodical within the volume

September

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

9

Pages from-to

182-190

UT code for WoS article

000409290400020

EID of the result in the Scopus database

2-s2.0-85021174952