SSVEP-Based Brain-Computer Interface for Cursor Control
Design and Implementation of a Data Acquisition Pipeline for SSVEP-Based BCI
W. Khiar (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Y. Alami (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Dante G Muratore – Mentor (TU Delft - Bio-Electronics)
T. Costa – Mentor (TU Delft - Bio-Electronics)
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Abstract
This project explores the development of a real-time Brain-Computer Interface (BCI) system based on Steady-State Visually Evoked Potentials (SSVEPs). The aim is to enable hands-free computer control by detecting brain responses to visual stimuli flickering at specific frequencies. Our focus was on the acquisition of clean and stable EEG signals using the Unicorn Hybrid Black headset. Key challenges included minimizing noise from motion and eye artifacts, selecting the right channels for SSVEP detection, and applying appropriate filters. While the hardware setup and real-time streaming via Lab Streaming Layer (LSL) were successfully established, consistent frequency detection during visual stimulus trials remains an unresolved issue. Controlled tests with simulated signals confirmed that the pipeline can detect known inputs, indicating that future work should focus on improving artifact removal and stimulus reliability. The current system provides a solid foundation for further development toward robust, real-time brain-controlled interfaces