Application of artificial neural networks for analyses of EEG record with semi-automated etalons extraction: A pilot study

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00023752%3A_____%2F16%3A43915395" target="_blank" >RIV/00023752:_____/16:43915395 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21230/16:00304845 RIV/68407700:21460/16:00304845 RIV/68407700:21730/16:00304845 RIV/61989100:27240/16:86097740

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007%2F978-3-319-44188-7_7" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-319-44188-7_7</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-44188-7_7" target="_blank" >10.1007/978-3-319-44188-7_7</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Application of artificial neural networks for analyses of EEG record with semi-automated etalons extraction: A pilot study

Popis výsledku v původním jazyce

Application of artificial neural network (ANN) classification - multilayer perceptron (MLP) with simulated annealing for initialization and genetic algorithm for weight optimization on multi-channel EEG record is presented here. The novelty of the approach lies in the semi-automated etalon extraction. The etalons are suggested by the k-means algorithm and verified/edited by an expert. The whole process of EEG record consists of multichannel adaptive segmentation, feature extraction from segments, semi-automatic process of etalons extraction by the k-means cluster analysis leading to color segment identification and continuing with manual choice of segments for etalons by the expert and feature extraction of chosen etalons. Subsequent classification by ANN leads to unique color identification of segments in the EEG record and additionally in temporal profile. Our goal is to help the physician by mimetic software because the examination of long multichannel EEG is a tedious work.

Název v anglickém jazyce

Application of artificial neural networks for analyses of EEG record with semi-automated etalons extraction: A pilot study

Popis výsledku anglicky

Application of artificial neural network (ANN) classification - multilayer perceptron (MLP) with simulated annealing for initialization and genetic algorithm for weight optimization on multi-channel EEG record is presented here. The novelty of the approach lies in the semi-automated etalon extraction. The etalons are suggested by the k-means algorithm and verified/edited by an expert. The whole process of EEG record consists of multichannel adaptive segmentation, feature extraction from segments, semi-automatic process of etalons extraction by the k-means cluster analysis leading to color segment identification and continuing with manual choice of segments for etalons by the expert and feature extraction of chosen etalons. Subsequent classification by ANN leads to unique color identification of segments in the EEG record and additionally in temporal profile. Our goal is to help the physician by mimetic software because the examination of long multichannel EEG is a tedious work.

Druh

D - Stať ve sborníku

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

—

Projekt

—

Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

17th International Conference on Engineering Applications of Neural Networks, EANN 2016; Aberdeen; United Kingdom; 2 September 2016 through 5 September 2016

ISBN

978-3-319-44187-0

ISSN

1865-0929

e-ISSN

—

Počet stran výsledku

14

Strana od-do

94-107

Název nakladatele

Springer International Publishing

Místo vydání

Cham

Místo konání akce

Aberdeen; United Kingdo

Datum konání akce

2. 9. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—