Inter-Session Robust Hybrid Brain-Computer Interface: Safe and User-Friendly Approach with LED Activation Mechanism

This study introduces, a hybrid BCI system with a robust and secure activation mecha-nism between sessions is introduced, aiming to minimize the negative effects of visual stimulus-based Brain-Computer Interface (BCI) systems on user eye health. The system is based on the integration of Electroencephalography (EEG) signals and Electrooculography (EOG) artefacts, and includes an LED stimulus operating at a frequency of 7Hz for safe ac-tivation and objects moving in different directions. While the LED functions as an activa-tion switch that reduces visual fatigue caused by traditional visual stimuli, moving objects provide command generation depending on the user's intention. In order to evaluate the stability of the system against physiological and psychological conditions, data were col-lected from 15 participants in two different sessions. Correlation Alignment (CORAL) method was applied to the data to reduce the variance between sessions and to increase stability. Bootstrap Aggregating algorithm was used in the classification processes and with the CORAL method, the system accuracy rate was increased from 81.54% to 94.29%. The results show that the proposed system offers a safe activation infrastructure that can effectively adapt to users' changing cognitive states throughout the day by reducing visual fatigue, along with its high accuracy and stability.