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One of the most used signals in Brain Machine Interfaces (BMI) is the Steady State Visually Evoked Potentials (SSVEP). In a SSVEP-based BMI, a visual stimulus that flickers in a constant frequency is presented to the user, and the system has to detect if the user is gazing the stimulus. Usually the stimulus is a rectangular signal and there are no clear criteria for select the duty cycle, which is generally fixed to 50 %. We propose a model for SSVEP that links the phase and amplitude variations in function of the duty cycle for a specific frequency. This model can be adjusted using only the phase of the SSVEP signal and it could improve the SSVEP-based BMI by selecting the duty cycle. The model was fixed for SSVEP responses in a man who is 39 years old. The mean absolute error below 0.3 rad shows that the model predicts the phase in the majority of the used frequencies.
Silvestro Micera, Solaiman Shokur, Daniel Jose Lins Leal Pinheiro