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Data released on May 05, 2017

Supporting data for "EEG datasets for motor imagery brain computer interface"

Ahn, M; Ahn, S; Cho, H; Jun, S, C; Kwon, M (2017): Supporting data for "EEG datasets for motor imagery brain computer interface" GigaScience Database. http://dx.doi.org/10.5524/100295 RIS BibTeX Text

Most investigators of brain computer interface (BCI) 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 generate induced activity by imagining motor movements. However, variations in performance over sessions and subjects are too severe to overcome easily; therefore, a basic understanding and investigation of BCI performance variation is necessary to find critical evidence of performance variation.
Here we present not only EEG datasets for MI BCI from 52 subjects, but also the results of a psychological and physiological questionnaire, EMG datasets, the locations of 3D EEG electrodes, and EEGs for non-task related states.
We validated our EEG datasets by using the percentage of bad trials, event-related desynchronization/synchronization (ERD/ERS) analysis, and classification analysis. After conventional rejection of bad trials, we showed contralateral ERD and ipsilateral ERS in the somatosensory area, which are well-known patterns of MI. Finally, we showed that 73.08% of datasets (38 subjects) included reasonably discriminative information.
Our EEG datasets included information necessary to determine statistical significance; they consisted of well-discriminated datasets (38 subjects) and less-discriminative datasets. These may provide researchers with opportunities to investigate human factors related to MI BCI performance variation, and may also achieve subject-to-subject transfer by using metadata, including a questionnaire, EEG coordinates, and EEGs for non-task related states.

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Related manuscripts:

doi:10.1093/gigascience/gix034

Keywords:

Motor imagery EEG brain computer interface performance variation subject-to-subject transfer 

ElectroEncephaloGraphy(EEG)

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Samples: Table Settings

Columns:

Common Name
Scienfic Name
Sample Attributes
Taxonomic ID
Genbank Name

Sample IDTaxonomic IDCommon NameGenbank NameScientific NameSample Attributes
s219606HumanhumanHomo sapiens Description:Right handed 20 year old Male particip...
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s229606HumanhumanHomo sapiens Description:Right handed 19 year old Male particip...
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s239606HumanhumanHomo sapiens Description:Right handed 19 year old Male particip...
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s249606HumanhumanHomo sapiens Description:Right handed 25 year old Male particip...
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s259606HumanhumanHomo sapiens Description:Right handed 25 year old Female partic...
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s269606HumanhumanHomo sapiens Description:Right handed 26 year old Male particip...
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s279606HumanhumanHomo sapiens Description:Right handed 33 year old Male particip...
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s289606HumanhumanHomo sapiens Description:Right handed 19 year old Male particip...
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s299606HumanhumanHomo sapiens Description:Right handed 20 year old Male particip...
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s309606HumanhumanHomo sapiens Description:Right handed 29 year old Male particip...
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Displaying 21-30 of 52 Sample(s).

Files: (FTP site) Table Settings

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File Description
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Download Link
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File NameSample IDFile TypeFile FormatSizeRelease Date 
Tabular dataEXCEL26.7 KB2017-04-06
ReadmeTEXT2.18 KB2017-04-06
s1MatLabUNKNOWN194.02 MB2017-04-06
s2MatLabUNKNOWN195.84 MB2017-04-06
s3MatLabUNKNOWN196.98 MB2017-04-06
s4MatLabUNKNOWN191.17 MB2017-04-06
s5MatLabUNKNOWN194.75 MB2017-04-06
s6MatLabUNKNOWN192.39 MB2017-04-06
s7MatLabUNKNOWN222.73 MB2017-04-06
s8MatLabUNKNOWN193.23 MB2017-04-06
Displaying 1-10 of 54 File(s).

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