Fast BCI Calibration - Comparing Methods to Adapt BCI Systems for New Subjects

A Brain Computer Interface (BCI) is a system where a direct connection is established between the brain and a computer, providing a subject with a new communication channel. Unfortunately, BCI have many drawbacks: signal recording is problematic, brain signatures are non reproducible from individual to individual, etc. A dependent-BCI prototype, the BrainPC project, was developed in the SIGMA laboratory. Electroencephalographic (EEG) signals collected by a BrainAmp amplifier in responses to flickering light stimuli (Steady State Visual Evoked Potentials) are converted into machine-readable commands. This system is coupled with a human-machine interface. We propose a solution for fast calibration of the automatic detection of SSVEP between experimental subjects. We tested different calibration methods; harmonic and electrode selections were shown to be the most efficient methods.

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