  We present a mobile dataset obtained from electroencephalography (EEG) of the
scalp and around the ear as well as from locomotion sensors by 24 participants
moving at four different speeds while performing two brain-computer interface
(BCI) tasks. The data were collected from 32-channel scalp-EEG, 14-channel
ear-EEG, 4-channel electrooculography, and 9-channel inertial measurement units
placed at the forehead, left ankle, and right ankle. The recording conditions
were as follows: standing, slow walking, fast walking, and slight running at
speeds of 0, 0.8, 1.6, and 2.0m/s, respectively. For each speed, two different
BCI paradigms, event-related potential and steady-state visual evoked
potential, were recorded. To evaluate the signal quality, scalp- and ear-EEG
data were qualitatively and quantitatively validated during each speed. We
believe that the dataset will facilitate BCIs in diverse mobile environments to
analyze brain activities and evaluate the performance quantitatively for
expanding the use of practical BCIs.
