شماره ركورد كنفرانس :
3751
عنوان مقاله :
Comparison between different methods of feature extraction in BCI systems based on SSVEP
پديدآورندگان :
Sheykhivand Sobhan s.sheykhivand@gmail.com Department of Electrical and Computer Engineering University of Tabriz, Tabriz, Iran , Yousefi rezaii Tohid yousefi@tabrizu.ac.ir Department of Electrical and Computer Engineering University of Tabriz, Tabriz, Iran , Naderi Saatlo Ali a.naderi@iaurmia.ac.ir Department of Electrical-Electronics Engineering Urmia Branch, Islamic Azad University, Urmia, Iran , Romooz Nikoo nikoo.romoz96@gmail.com Department of Electrical-Electronics Engineering Urmia Branch, Islamic Azad University, Urmia, Iran
كليدواژه :
BCI , CCA , Cross Correlation , FFT , Fuzzy , HHT , PSDA , SSVEP.
عنوان كنفرانس :
دومين كنفرانس ملي رياضي: مهندسي پيشرفته با تكنيك هاي رياضي
چكيده فارسي :
There are different feature extraction methods in brain-computer interfaces (BCI) based on Steady-State Visually Evoked Potentials (SSVEP) systems. This paper presents a comparison of five methods for stimulation frequency detection in SSVEP-based BCI systems. The techniques are based on Power Spectrum Density Analysis (PSDA), Fast Fourier Transform (FFT), Hilbert- Huang Transform (HHT), Cross Correlation and Canonical Correlation Analysis (CCA). The results demonstrate that the CCA and FFT can be successfully applied for stimulus frequency detection by considering the highest accuracy and minimum consuming time.
