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>