Wyniki wyszukiwania - Biblioteka Nauki

1

Metoda LORETA jako przykład metody rozwiązywania zagadnienia odwrotnego w interfejsie mózg-komputer

100%

Jagodzińska U. , Oskwarek Ł.

Elektronika : konstrukcje, technologie, zastosowania

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2012

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tom Vol. 53, nr 12

89-91

PL

Metody rejestrowania elektrycznych i magnetycznych aktywności mózgu jak elektroencefalografia (EEG) lub magnetoencefalografia (MEG) nie dają pełnej informacji o źródle rejestrowanych sygnałów. Przyjmując uproszczony model źródeł jako dipoli prądowych umieszczonych w różnych punktach mózgu, trzeba mieć na uwadze, że istnieje nieskończenie wiele różnych konfiguracji tych źródeł, które generują taki sam rozkład potencjałów na powierzchni czaszki. Przeprowadzane testy, w których porównywano wyniki poszukiwań źródeł aktywności, dały najlepsze wyniki dla metody LORETA, np. przedstawione w pracy Pascual-Marqui R. D.

EN

Methods of register electrical and magnetic brain activities as electroencephalography (EEG) or magnetoencefalography (MEG) do not give information about exact sources of registered signals. If is assumed a simplified model of sources as current dipole placed at different points of the brain, it should be taken into account that there are infinitely many different configurations of these sources which generate the same distribution of potentials on the surface of the skull. Tests carried out for solving the EEG inverse problem which compared the results of exploration activity sources gave the best results for the LORETA method, examples in paper Pascual- Marqui R. D.

2

Barokní poutní cesta do Hájku u Prahy

94%

Pařízková K.

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nr 2

113-153

EN

The essay is dedicated to the Baroque pilgrim route from Prague to the Loreta which is still standing in the Franciscans’ monastery in Hajek u Červeneho Ujezda. It originated in 1720-1733. Twenty alcove chapels in a regular spacing were built at the expense of leading noble families. Inside Theky were painted with murals depicting the lives of the Virgin Mary and St. Francis. The Franciscan order maintained and repaired them until the end of the 18th century. When the resources for thein repairs were stopped, the order had no finances for their maintenance. Six of them were pulled down in the course of the 19th century because of their bad condition. Eleven chapels have survived and have been gradually repaired. A section of the broken pilgrim route between Litovice and Hajek has been restored.

3

Using LORETA Method Based on the EEG Signal for Localizing the Sources of Brain Waves Activity

94%

Paszkiel S.

Measurement Automation Monitoring

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2016

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tom Vol. 62, No. 8

262--264

EN

The article presents the possibility of using the method of imaging brain activity, LORETA LOw Resolution Electromagnetic TomogrAphy), that can base on electroencephalographical and magnetoencephalographical readings. Thanks to using the above-mentioned method, it is possible to localize the sources of the activity of individual signals registered on the head surface. This is very significant regarding construction of the brain-computer interfaces in order to conduct proper identification and classification of signals obtained during electroencephalography.

4

Independent component analysis of EEG data for EGI system

83%

Gajos A. , Wójcik G. M.

Bio-Algorithms and Med-Systems

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2016

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tom Vol. 12, no. 2

67--72

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.

5

An attempt to localize brain electrical activity sources using EEG with limited number of electrodes

67%

Majkowski A. , Oskwarek Ł. , Kołodziej M. , Rak R. J.

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tom Vol. 36, no. 4

686--696

EN

A very interesting research goal is to find underlying sources generating the EEG signal–referred to as the ‘‘EEG inverse problem’’. Its aim is to determine spatial distribution of brain activity, described by local brain currents density, on the basis of potentials measured on the scalp as EEG signal. The purpose of the research presented in the article was to check whether the results of the inverse problem solution, obtained by the LORETA algorithm for the reduced set of 8 electrodes selected by the authors will be close to the results for the initial set of 32 electrodes. EEG signals were registered during the BCI operation based on ERD/ERS potentials. Obtained results showed no significant differences in the location of the most important sources in both cases. It is worth emphasizing that reducing the number of electrodes would have a significant impact on an BCI ergonomics.