Mobile BCI dataset of scalp- and ear-EEGs with ERP and SSVEP paradigms while standing, walking, and running

Young-Eun Lee; Gi-Hwan Shin; Minji Lee; Seong-Whan Lee

doi:10.1038/s41597-021-01094-4

Scientific Data (Dec 2021)

Mobile BCI dataset of scalp- and ear-EEGs with ERP and SSVEP paradigms while standing, walking, and running

Young-Eun Lee,
Gi-Hwan Shin,
Minji Lee,
Seong-Whan Lee

Affiliations

Young-Eun Lee: Korea University, Department of Brain and Cognitive Engineering
Gi-Hwan Shin: Korea University, Department of Brain and Cognitive Engineering
Minji Lee: Korea University, Department of Brain and Cognitive Engineering
Seong-Whan Lee: Korea University, Department of Brain and Cognitive Engineering

DOI: https://doi.org/10.1038/s41597-021-01094-4
Journal volume & issue: Vol. 8, no. 1
pp. 1 – 12

Abstract

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Measurement(s) brain activity measurement • angular velocity • acceleration • Magnetic Field Technology Type(s) electroencephalography (EEG) • Inertial measurement unit (IMU) Factor Type(s) stimuli frequency • speed of particpant Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.16669072

Published in Scientific Data

ISSN: 2052-4463 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/sdata/

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