SSVEP-Based Answer Selection Using a Low-Cost 8-Channel EEG System

In this work, the topic of neurogames was ex
plored. The focus was on cost-effectiveness and low com
plexity. A low-cost 8-channel EEG headset was used for sig
nal acquisition, with only the data from the occipital chan
nels (PO7, Oz, PO8) being utilised. A quiz was developed as
the game, in which participants had to select answer options
by focusing on visual stimuli flickering at different frequen
cies. The steady-state visual evoked potential was chosen as
the biosignal, which is triggered at the same frequencies as
the visual stimuli. Canonical correlation analysis (CCA) was
used for decision-making. In this process, the recorded sig
nal data is compared with the two frequencies used for the
stimuli. The answer option with the higher coefficient is then
selected. Compared to commonly used machine learning algo
rithms, this method places low demands on the hardware used.
Furthermore, it is not only fast to implement but also requires
no training data. The experiment was conducted twice: once
with the frequency pair 10 Hz and 17 Hz, and once with 6 Hz
and 17 Hz. Both trials achieved an accuracy of over 80%

DOI 10.1515/cdbme-2026-0170

OpenAlex ID W7215128506