Autor: Cysewska-Sobusiak, A. - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Stimuli design for SSVEP-based brain computer-interface
Autorzy:: Jukiewicz, M.
Cysewska-Sobusiak, A.
Powiązania:: https://bibliotekanauki.pl/articles/226402.pdf
Data publikacji:: 2016
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: EEG
OpenBCI
SSVEP
BCI
Opis:: The paper presents a process of stimuli design for SSVEP-based brain computer-interface. A brain computerinterface can be used in direct communication between a brain and a computer, without using muscles. This device is useful for paralyzed people to communicate with the surrounding environment. Design process should provide high accuracy recognition of presented stimuli and high user comfort. It is widely known how to make stimuli for BCI which are using high-grade EEG. Over recent years cheaper EEGs are becoming more and more popular, for example OpenBCI, which uses ADS1299 amplifier. In this article we review past works of other authors and compare it with our results, obtained using EEG mentioned before. We try to confirm that it is possible to use successfully OpenBCI in BCI projects.
Źródło:: International Journal of Electronics and Telecommunications; 2016, 62, 2; 109-113
2300-1933
Pojawia się w:: International Journal of Electronics and Telecommunications
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Finding Optimal Frequency and Spatial Filters Accompanying Blind Signal Separation of EEG Data for SSVEP-based BCI
Autorzy:: Jukiewicz, M.
Buchwald, M.
Cysewska-Sobusiak, A.
Powiązania:: https://bibliotekanauki.pl/articles/226812.pdf
Data publikacji:: 2018
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: BCI
SSVEP
BSS
FastICA
AMUSE
Infomax
Extended Infomax
CAR
Large Laplacian
Small Laplacian
CCA
Opis:: Brain-computer interface (BCI) is a device which allows paralyzed people to navigate a robot, prosthesis or wheelchair using only their own brains reactions. By creating a direct communication pathway between the human brain and a machine, without muscles contractions or activity from within the peripheral nervous system, BCI makes mapping persons intentions onto directive signals possible. One of the most commonly utilized phenomena in BCI is steady-state visually evoked potentials (SSVEP). If subject focuses attention on the flashing stimulus (with specified frequency) presented on the computer screen, a signal of the same frequency will appear in his or hers visual cortex and from there it can be measured. When there is more than one stimulus on the screen (each flashing with a different frequency) then based on the outcomes of the signal analysis we can predict at which of these objects (e.g., rectangles) subject was/is looking at that particular moment. Proper preprocessing steps have taken place in order to obtain maximally accurate stimuli recognition (as the specific frequency). In the current article, we compared various preprocessing and processing methods for BCI purposes. Combinations of spatial and temporal filtration methods and the proceeding blind source separation (BSS) were evaluated in terms of the resulting decoding accuracy. Canonical-correlation analysis (CCA) to signals classification was used.
Źródło:: International Journal of Electronics and Telecommunications; 2018, 64, 4; 439-444
2300-1933
Pojawia się w:: International Journal of Electronics and Telecommunications
Dostawca treści:: Biblioteka Nauki

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