Independent component analysis of EEG data for EGI system

• Autorzy: Gajos A. , Wójcik G. M.

Identyfikatory

DOI

10.1515/bams-2016-0004

• Języki publikacji: EN

Abstrakty

EN

Component analysis is one of the most important methods used for electroencephalographic (EEG) signal decomposition, and the so-called independent component analysis (ICA) is commonly used. The main function of the ICA algorithm is to find a linear representation of non-Gaussian data whose elements are statistically independent or at least as independent as possible. There are many commercial solutions for EEG signal acquisition. Usually, together with the EEG, one gets a dedicated software to handle the signal. However, quite often, the software does not provide researchers with all necessary functions. A high-performance, dense-array EGI-EEG system is distributed with the NetStation software. Although NetStation is a powerful tool, it does not have any implementation of the ICA algorithm. This causes many problems for researchers who want to export raw data from the amplifier and then work on it using some other tools such as EEGLAB for MATLAB, as these data are not fully compatible with the EGI format. We will present the C++ implementation of ICA that can handle filtered data from the EGI with better affordability. Our tool offers visualization of raw signal and ICA algorithm results and will be distributed under Freeware license.

Słowa kluczowe

EN

EEG; EGI; ICA; LORETA; source localisation

• Wydawca: Uniwersytet Jagielloński - Collegium Medicum ; Index Copernicus Sp. z o.o.
• Czasopismo: Bio-Algorithms and Med-Systems
• Rocznik: 2016
• Tom: Vol. 12, no. 2
• Strony: 67--72
• Opis fizyczny: Bibliogr. 21 poz., rys., wykr.

Twórcy

autor

Gajos A.

• Laboratory of Neuroinformatics, Maria Curie- Sklodowska University, Lublin, Poland

autor

Wójcik G. M.

• Laboratory of Neuroinformatics, Maria Curie-Sklodowska University, Akademicka 9, Lublin 20-033, Poland
• Department of Transport and Computer Science, University of Economics and Innovation, Lublin, Poland

Bibliografia

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Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.