Temat: brain-computer interface - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Implementation of Bilinear Separation algorithm as a classification method for SSVEP-based brain-computer interface
Autorzy:: Jukiewicz, M.
Cysewska-Sobusiak, A.
Powiązania:: https://bibliotekanauki.pl/articles/114357.pdf
Data publikacji:: 2015
Wydawca:: Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:: brain-computer interface
SSVEP
bilinear separation
support vector machine (SVM)
Opis:: : The aim of this study was to create a two-class brain-computer interface. As in the case of research on SSVEP stimuli flashing at different frequencies were presented to four subjects. Optimal SSVEP recognition results can be obtained from electrodes: O1, O2 and Oz. In this work SVM classifier with Bilinear Separation algorithm have been compared. The best result in the offline tests using Bilinear Separation was: average accuracy of stimuli recognition 93% and ITR 33.1 bit/min, SVM: 90% and 32.8 bit/min.
Źródło:: Measurement Automation Monitoring; 2015, 61, 2; 51-53
2450-2855
Pojawia się w:: Measurement Automation Monitoring
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Low-cost evoked potentials detection for brain computer-interfaces
Autorzy:: Jukiewicz, M.
Cysewska-Sobusiak, A.
Powiązania:: https://bibliotekanauki.pl/articles/97604.pdf
Data publikacji:: 2015
Wydawca:: Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
Tematy:: brain-computer interface
detection of evoked potentials
EEG
signal processing
MATLAB
Opis:: Evoked potentials are one of the brain's electrical activity types. They appear on the human scalp as a result of a registration of an external stimulus (e.g. an appearance or a change of a sound, a flash of light or an image). Generally, they are used in medical diagnosis, but they also may be used in brain-computer interfaces. In this chapter a laboratory set for the acquisition and analysis of evoked potentials is described. The main part of this set is a photostimulator consisting of sixteen LEDs and the ATmega 328 microcontroller. The software created by the authors allows for: connection between EEG device, stimulator and computer, input stimulus control, output signal filtering and its classification. The presented set may support a process of brain-computer interface design.
Źródło:: Computer Applications in Electrical Engineering; 2015, 13; 102-110
1508-4248
Pojawia się w:: Computer Applications in Electrical Engineering
Dostawca treści:: Biblioteka Nauki

Artykuł

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