Implementation of Bilinear Separation algorithm as a classification method for SSVEP-based brain-computer interface

• Autorzy: Jukiewicz M. , Cysewska-Sobusiak A.
• Języki publikacji: EN

Abstrakty

EN

: 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.

Słowa kluczowe

EN

brain-computer interface; SSVEP; bilinear separation; support vector machine (SVM)

• Wydawca: Wydawnictwo PAK
• Czasopismo: Measurement Automation Monitoring
• Rocznik: 2015
• Tom: Vol. 61, No. 2
• Strony: 51--53
• Opis fizyczny: Bibliogr. 10 poz., rys., tab., wykr., wzory

Twórcy

autor

Jukiewicz M.

• Poznan University of Technology, Institute of Electrical Engineering and Electronics, Division of Metrology and Optoelectronic, Piotrowo 3a, 60-965 Poznan

autor

Cysewska-Sobusiak A.

• Poznan University of Technology, Institute of Electrical Engineering and Electronics, Division of Metrology and Optoelectronic, Piotrowo 3a, 60-965 Poznan

Bibliografia

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