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https://github.com/shimazadeh/total-perspective-vortex

This subject aims to create a brain computer interface based on electroencephalographic data (EEG data) with the help of machine learning algorithms. Using a subject’s EEG reading, you’ll have to infer what he or she is thinking about or doing - (motion) A or B in a t0 to tn timeframe.
https://github.com/shimazadeh/total-perspective-vortex

ai algorithm classification datascience dimensionality-reduction eeg scikit-learn

Last synced: about 2 months ago
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This subject aims to create a brain computer interface based on electroencephalographic data (EEG data) with the help of machine learning algorithms. Using a subject’s EEG reading, you’ll have to infer what he or she is thinking about or doing - (motion) A or B in a t0 to tn timeframe.

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# Total-perspective-vortex

This subject aims to create a brain computer interface based on electroencephalographic data (EEG data) with the help of machine learning algorithms. Using a subject’s EEG reading, we infer what he or she is thinking about or doing - (motion) A or B in a t0 to tn timeframe.



# Data folder

The data folder include 109 subjects. each subjects has 14 file representing the 14 tasks listed in the next section



# Experimental Protocol

Subjects performed different motor/imagery tasks while 64-channel EEG were recorded using the BCI2000 system (http://www.bci2000.org). Each subject performed 14 experimental runs: two one-minute baseline runs (one with eyes open, one with eyes closed), and three two-minute runs of each of the four following tasks:



- A target appears on either the left or the right side of the screen. The subject opens and closes the corresponding fist until the target disappears. Then the subject relaxes.

- A target appears on either the left or the right side of the screen. The subject imagines opening and closing the corresponding fist until the target disappears. Then the subject relaxes.

- A target appears on either the top or the bottom of the screen. The subject opens and closes either both fists (if the target is on top) or both feet (if the target is on the bottom) until the target disappears. Then the subject relaxes.

- A target appears on either the top or the bottom of the screen. The subject imagines opening and closing either both fists (if the target is on top) or both feet (if the target is on the bottom) until the target disappears. Then the subject relaxes.



In summary, the experimental runs were:



- R01: Baseline, eyes open

- R02: Baseline, eyes closed

- R03: Task 1 (open and close left or right fist)

- R04: Task 2 (imagine opening and closing left or right fist)

- R05: Task 3 (open and close both fists or both feet)

- R06: Task 4 (imagine opening and closing both fists or both feet)

- R07: Task 1 

- R08: Task 2

- R09: Task 3

- R10: Task 4

- R11: Task 1

- R12: Task 2

- R13: Task 3

- R14: Task 4



The data are provided here in EDF+ format (containing 64 EEG signals, each sampled at 160 samples per second, and an annotation channel). For use with PhysioToolkit software, rdedfann generated a separate PhysioBank-compatible annotation file (with the suffix .event) for each recording. The .event files and the annotation channels in the corresponding .edf files contain identical data.



Each annotation includes one of three codes (T0, T1, or T2):



- T0 corresponds to rest

- T1 corresponds to onset of motion (real or imagined) of

the left fist (in runs 3, 4, 7, 8, 11, and 12)

both fists (in runs 5, 6, 9, 10, 13, and 14)

- T2 corresponds to onset of motion (real or imagined) of

the right fist (in runs 3, 4, 7, 8, 11, and 12)

both feet (in runs 5, 6, 9, 10, 13, and 14)



[Link to My Jupyter Notebook](Notebook.ipynb)