A-Generalizable-BCI-using-Machine-Learning-for-Feature-Discovery-masterzip. (229.31 MB)
A Generalizable BCI using Machine Learning for Feature Discovery
The first variable is data_key_'participant letter', which takes the value 1,2 or 3, depending on if they didn't squeeze their hand, squeezed right or squeezed left during that epoch.
The second is data_epochs_'participant letter'. This is the EEG data corresponding to the data key.
The first dimension is all the channels (62 channels for the first two sets) concatenated into a single row, so there's 100 data points for each channel for each epoch.