EEG datasets for motor imagery brain–computer interface

• Published in: Gigascience Vol. 6; no. 7; pp. 1 - 8
• Main Authors: Cho, Hohyun, Ahn, Minkyu, Ahn, Sangtae, Kwon, Moonyoung, Jun, Sung Chan
• Format: Journal Article
• Language: English
• Published: United States Oxford University Press 01.07.2017
• Subjects: Adult; Biochips; Brain; Brain-Computer Interfaces; Cerebral Cortex - physiology; Computer applications; Data Note; Datasets; Datasets as Topic - standards; EEG; Electroencephalography; Electroencephalography - methods; Electroencephalography - standards; Female; Human factors; Human-computer interface; Humans; Imagery; Imagination; Implants; Male; Mental task performance; Movement; Questionnaires; Software; Somatosensory cortex; Synchronism; Synchronization; Variation; motor imagery; brain–computer interface; EEG; subject-to-subject transfer; performance variation

Abstract Background: Most investigators of brain–computer interface (BCI) research believe that BCI can be achieved through induced neuronal activity from the cortex, but not by evoked neuronal activity. Motor imagery (MI)–based BCI is one of the standard concepts of BCI, in that the user can genera...