Fuzzy ensemble decision making for SSVEP-based BCI systems

There are different feature extraction methods in brain-computer interfaces (BCI) based on Steady-state visually evoked potentials (SSVEP) systems. In this study, Fuzzy ensemble has been used to stimulation frequency detection and we used outputs of CCA and FFT features as input of Fuzzy ensemble. This model has been used to select best method to detect stimulation frequency. The result of study recommends that the Fuzzy models can be successfully selected as an appropriate method to stimulation frequency detection in BCI systems based on SSVEP.

Keywords:

BCI , SSVEP , CCA , FFT , Fuzzy model