A comparative study of different feature extraction methods in SSVEP-based BCI systems
عنوان مقاله: A comparative study of different feature extraction methods in SSVEP-based BCI systems
شناسه ملی مقاله: CBCONF01_0789
منتشر شده در اولین کنفرانس بین المللی دستاوردهای نوین پژوهشی در مهندسی برق و کامپیوتر در سال 1395
شناسه ملی مقاله: CBCONF01_0789
منتشر شده در اولین کنفرانس بین المللی دستاوردهای نوین پژوهشی در مهندسی برق و کامپیوتر در سال 1395
مشخصات نویسندگان مقاله:
Najmeh Salmani Bafrouei - Biomedical Engineering Department Semnan University, Semnan, Iran
Ali Maleki - Biomedical Engineering Department Semnan University, Semnan, Iran
خلاصه مقاله:
Najmeh Salmani Bafrouei - Biomedical Engineering Department Semnan University, Semnan, Iran
Ali Maleki - Biomedical Engineering Department Semnan University, Semnan, Iran
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 through 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). Results demonstrate that the CCA and FFT can be successfully applied for stimulus frequency detection by considering the highest accuracy and minimum consuming time.
کلمات کلیدی: BCI, CCA, Cross Correlation, FFT, Fuzzy, HHT, PSDA, SSVEP
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/497244/