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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
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Genbank Name

Sample IDTaxonomic IDCommon NameGenbank NameScientific NameSample Attributes
s29606HumanhumanHomo sapiens Description:Right handed 29 year old Male particip...
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s39606HumanhumanHomo sapiens Description:Right handed 23 year old Female partic...
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s49606HumanhumanHomo sapiens Description:Right handed 31 year old Male particip...
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s59606HumanhumanHomo sapiens Description:Right handed 20 year old Male particip...
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s69606HumanhumanHomo sapiens Description:Right handed 27 year old Male particip...
Age:27
Sex:Male
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s79606HumanhumanHomo sapiens Description:Right handed 26 year old Male particip...
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Sex:Male
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s89606HumanhumanHomo sapiens Description:Right handed 20 year old Male particip...
Age:20
Sex:Male
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s99606HumanhumanHomo sapiens Description:Right handed 24 year old Male particip...
Age:24
Sex:Male
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s109606HumanhumanHomo sapiens Description:Right handed 18 year old Male particip...
Age:18
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s19606HumanhumanHomo sapiens Description:Right handed 24 year old Female partic...
Age:24
Sex:Female
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Displaying 1-10 of 52 Sample(s).

Files: (FTP site) Table Settings

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File Description
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File Type
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Release Date
Download Link
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File NameSample IDFile TypeFile FormatSizeRelease Date 
s19MatLabUNKNOWN197.66 MB2017-04-06
s20MatLabUNKNOWN192.68 MB2017-04-06
s21MatLabUNKNOWN193.31 MB2017-04-06
s22MatLabUNKNOWN194.15 MB2017-04-06
s23MatLabUNKNOWN195.75 MB2017-04-06
s24MatLabUNKNOWN193.51 MB2017-04-06
s25MatLabUNKNOWN195.56 MB2017-04-06
s26MatLabUNKNOWN193.61 MB2017-04-06
s27MatLabUNKNOWN195.3 MB2017-04-06
s28MatLabUNKNOWN196.03 MB2017-04-06
Displaying 21-30 of 54 File(s).

History:

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