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Description
Electroencephalographic (EEG) signals were acquired from 17 (14 males, 3 females) participants aged between 20 and 30 years.
The input data were gathered for the signal processing algorithms during sessions lasting for approximately 20 minutes. Each session consisted of three tasks performed by the subjects:
- relaxation with closed eyes - before this task execution the subjects were asked to relax in order to induce mental states associated with such an activity,
- watching a music video - music genre chosen for this task was folk metal due to the engaging and lively character of this music style which creates an opportunity to induce mental states that were being of an opposite type to those ones in the preceding task,
- playing a logic game, the game used at this stage of the experiment was Netwalk logic computer game, in which a player had to rotate elements of the board in such a manner, that a connection was being established between a single central element called server and multiple peripheral elements called computers.
The data is stored in EDF (European Data Format) file format.
Dataset file
hexmd5(md5(part1)+md5(part2)+...)-{parts_count} where a single part of the file is 512 MB in size.Example script for calculation:
https://github.com/antespi/s3md5
File details
- License:
-
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CC BYAttribution
Details
- Year of publication:
- 2020
- Verification date:
- 2020-12-17
- Dataset language:
- English
- Fields of science:
-
- information and communication technology (Engineering and Technology)
- biomedical engineering (Engineering and Technology)
- medical sciences (Medical and Health Sciences )
- DOI:
- DOI ID 10.34808/fdtt-sv97 open in new tab
- Verified by:
- Gdańsk University of Technology
Keywords
References
- publication Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
- publication Method for Clustering of Brain Activity Data Derived from EEG Signals
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