This thesis presents the design and implementation of a graphical user interface (GUI) for a real-time brain-computer interface (BCI) system based on steady-state visual evoked potentials (SSVEP). Developed as part of a larger collaborative project alongside Data Acquisition and
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This thesis presents the design and implementation of a graphical user interface (GUI) for a real-time brain-computer interface (BCI) system based on steady-state visual evoked potentials (SSVEP). Developed as part of a larger collaborative project alongside Data Acquisition and Signal Processing subgroups, the GUI enables users to control a computer cursor using brain activity. Core functionalities include real-time EEG visualization, configurable data recording trials, visual stimulus presentation, and a cursor control interface that provides feedback based on live classification results. The system architecture allows the GUI to connect to the EEG headset via the Lab Streaming Layer (LSL) protocol, stream EEG data to the back-end pipeline, and translate classification output into interactive visual feedback. The integrated system successfully demonstrated real-time SSVEP-based control, validating both functional and technical requirements of the GUI subsystem. This work contributes to the development of more intuitive and accessible GUI designs for future BCI applications.