Feature analysis of EEG signals using SOM

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F11%3A43882847" target="_blank" >RIV/60461373:22340/11:43882847 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Feature analysis of EEG signals using SOM

Popis výsledku v původním jazyce

The electroencephalogram (EEG) represents an e?cient technique to measure and record brain electrical activity. The most common use of EEG includes the monitoring and diagnosis of the brain states and their disorders. It is based on the search of characteristic patterns in EEG signals and their evaluation. In terms of signal processing it uses feature analysis, more speci?cally feature extraction and classi?cation of signal components. The paper deals with the feature study of EEG signals by the self-organizing neural network (SOM). The SOM is an unsupervised method using a neighborhood function to preserve the topological properties of the input space. Resulting algorithm was implemented in MATLAB with many optional parameters that provide possibilityto adjust the model to user's equirements. The graphical user interface was designed as well. General problems of feature analysis, such as extraction of appropriate characteristic features or evaluation of quality of clusters, were also

Název v anglickém jazyce

Feature analysis of EEG signals using SOM

Popis výsledku anglicky

The electroencephalogram (EEG) represents an e?cient technique to measure and record brain electrical activity. The most common use of EEG includes the monitoring and diagnosis of the brain states and their disorders. It is based on the search of characteristic patterns in EEG signals and their evaluation. In terms of signal processing it uses feature analysis, more speci?cally feature extraction and classi?cation of signal components. The paper deals with the feature study of EEG signals by the self-organizing neural network (SOM). The SOM is an unsupervised method using a neighborhood function to preserve the topological properties of the input space. Resulting algorithm was implemented in MATLAB with many optional parameters that provide possibilityto adjust the model to user's equirements. The graphical user interface was designed as well. General problems of feature analysis, such as extraction of appropriate characteristic features or evaluation of quality of clusters, were also

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2011

Kód důvěrnosti údajů

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

Název periodika

Posterus

ISSN

1338-0087

e-ISSN

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Svazek periodika

4

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

SK - Slovenská republika

Počet stran výsledku

7

Strana od-do

1-7

Kód UT WoS článku

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EID výsledku v databázi Scopus

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