Using steady-state visually evoked potential (SSVEP) in brain-computer interface (BCI) systems is the subject of a lot of research. One of the most popular and widely used detection method is using a power spectral density analysis (PSDA). Lately there have been some new methods emerging, one of them is using canonical correlation analysis (CCA) which seems to have some promising improvements and advantages compared to traditional SSVEP detection methods, like better signal-to-noise ratio (SNR), lower inter-subject variability and the possibility to use harmonic frequencies, i.e., a serie of frequencies which have the same fundamental frequency. In this research two different SSVEP detection methods, one using PSDA and one using CCA are compared. The results show that the CCA-based detection method performs significantly better than the PSDA-based detection method. The increase of performance can in particular be seen when using harmonic frequencies. While the PSDA-based detection method has difficulties detecting harmonic frequencies, the CCA-based detection method is able to detect harmonic frequencies.
|Place of Publication||Enschede|
|Publisher||Centre for Telematics and Information Technology (CTIT)|
|Number of pages||12|
|Publication status||Published - 21 Feb 2011|
|Name||CTIT Technical Report Series|
|Publisher||Centre for Telematics and Information Technology, University of Twente|
- steady-state visually evoked potentials
- Human computer interaction
- Brain-Computer Interfaces
Hakvoort, G., Reuderink, B., & Obbink, M. (2011). Comparison of PSDA and CCA detection methods in a SSVEP-based BCI-system. (CTIT Technical Report Series; No. TR-CTIT-11-03). Enschede: Centre for Telematics and Information Technology (CTIT).