Comparison Between Different Methods of Feature Extraction in BCI Systems Based on SSVEP
محل انتشار: مجله بین المللی ریاضیات صنعتی، دوره: 9، شماره: 4
سال انتشار: 1396
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 59
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شناسه ملی سند علمی:
JR_IJIM-9-4_009
تاریخ نمایه سازی: 26 دی 1402
چکیده مقاله:
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.
نویسندگان
S. Sheykhivand
Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran
T. Yousefi Rezaii
Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.
A. Naderi Saatlo
Department of Electrical-Electronics Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran.
N. Romooz
Department of Electrical-Electronics Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran.