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Frequency recognition for SSVEP-BCI using reference signals with dominant stimulus frequency

Detection of frequency for steady-state visual evoked potentials (SSVEP) is addressed. We propose to use the combination of CCA and training data-based template matching between two level of data adaptive reference signals that can deal with the dominant frequency. On the basis of magnitude of stimulus frequency components, the dominant channels are selected. The recognition accuracy as well as the information transfer rate (ITR) of the proposed method are examined compared to the state-of-the-art recognition method.