Investigating the impact of calibration time on classifier accuracy in c-VEP BCI systems

In this study the impact of number of training EEG data, recorded in the calibration session, on the performance of various classifiers for code-modulated Visual Evoked Potentials (c-VEP) based Brain-Computer Interfaces (BCI) was evaluated.

This work was presented at the 25th Annual Alberta Biomedical Engineering Conference, organized in Banff, Alberta, Canada.