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Mobile BCI dataset of scalp- and ear-EEGs with ERP and SSVEP paradigms while standing, walking, and running
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Description: 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.
Citation:
Y.-E. Lee, G.-H. Shin, M. Lee, and S.-W. Lee, "Mobile BCI dataset of scalp- and ear-EEGs with ERP and SSVEP paradigms while standing, walking, and running," Scientific Data, Vol. 8, No. 315, 2021.
DOI: 10.1038/s41597-021-01094-4
Y.-E. Lee, N.-S. Kwak, S.-W. Lee, "A Real-Time Movement Artifact Removal Method for Ambulatory Brain-Computer Interfaces," IEEE Trans. on Neural Systems & Rehabi…
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