10.4225/49/557E3E38E8EE2
EWAN NURSE
EWAN
NURSE
Pip Karoly
Pip
Karoly
A Generalizable BCI using Machine Learning for Feature Discovery
The University of Melbourne
2015
Electroencephalography
EEG
Motor evoked potential
Neuroscience and Physiological Psychology
Neuroscience
2015-06-15 02:53:42
Dataset
https://melbourne.figshare.com/articles/dataset/A_Generalizable_BCI_using_Machine_Learning_for_Feature_Discovery/2000880
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.<div><br></div><div>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.</div><div><br></div><div><br></div>