[Dataset] EEG-IO

EEG dataset recording for 20 subjects for involuntary eye blinks (i.e., forced, when an external stimulation was given) collected on OpenBCI headset

Citing the Dataset

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The dataset is freely available for research use. Please cite the following publication if using

Mohit Agarwal, Raghupathy Sivakumar
BLINK: A Fully Automated Unsupervised Algorithm for Eye-Blink Detection in EEG Signals
2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton). IEEE, 2019.

Dataset Specifications

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• Sampling Frequency: 250.0 samples per second
• Electrodes: Fp1 and Fp2
• Total Subjects: 20
• Experiment: Subjects were asked to blink when an external stimulation was provided

Dataset Files

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Raw EEG data is stored as S<Sub_ID>_data.csv and corresponding labels are stored in S<Sub_ID>_labels.csv

Reading Data

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A script read_data.py is provided to read the dataset

Raw EEG data

Data is stored in a .csv format where column 0 represents time, and column 1 and 2 represents raw EEG potentials (in uV) for channel 1 (Fp1) and channel 2 (Fp2) respectively.

Labels

• The first line is corrupt, <n> where n represents the total number of corrupt intervals
• n following lines represent the start and end time of corrupt interval in seconds. A value of -1 means until the end.
• The next line is 'blinks' which marks the starting of blinks
• Blinks are arranged as <blink_time>, <code> where
  • <blink_time>: middle point of blink in seconds (where the minima appears in EEG)
  • <code>: 0 is normal blink, 1 is blink when stimulation was given, 2 is soft blink

Contact

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For any queries, contact Mohit Agarwal Email: [email protected]