https://pandarua220.github.io/CV/tags/bci/BCIHugo Blox Builder (https://hugoblox.com)en-usTue, 05 Nov 2024 00:00:00 +0000https://pandarua220.github.io/CV/media/icon_hu7729264130191091259.pnghttps://pandarua220.github.io/CV/tags/bci/https://pandarua220.github.io/CV/project/bci/Tue, 05 Nov 2024 00:00:00 +0000https://pandarua220.github.io/CV/project/bci/<p>Collected EEG signals from occipital regions using gold cup electrodes and a Cyton board (250 Hz).</p> <p>Applied Butterworth filters for noise reduction and extracted key EEG components (4–35 Hz).</p> <p>Implemented and compared CCA and FFT methods to decode SSVEP frequencies with high accuracy.</p> <p>Transmitted motion commands via Bluetooth to demonstrate reliable and precise human-machine interaction.</p> <p>Reference: Li, M.; He, D.; Li, C.; Qi, S. Brain–Computer Interface Speller Based on Steady-State Visual Evoked Potential: A Review Focusing on the Stimulus Paradigm and Performance. Brain Sci. 2021, 11, 450. <a href="https://doi.org/10.3390/brainsci11040450" target="_blank" rel="noopener">https://doi.org/10.3390/brainsci11040450</a></p>