Neural oscillations induced by IAPS pictures (session 23) - Open Research Data - Bridge of Knowledge

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Neural oscillations induced by IAPS pictures (session 23)

Description

The data were collected to perform research on the possibility of controlling the content displayed on the monitor screen using human emotional states extracted from EEG signals. The dataset contains recordings of 14-channel EEG signals gathered from seven persons aged 23 - 35 within 26 sessions, during which 45 different random photos, taken from the International Affective Picture System – IAPS collection, were presented. All sessions were collected using the Emotiv Epoc+ device at the 256 Hz sampling rate, equipped with 14 electrodes arranged according to the 10-20 standard system.

The dataset contains three files:
(1) session23_EEGLogger.csv,
(2) session23_emotion_picture_timestamp.csv,
(3) session23_power_brainwaves.csv.

The time-dependent (timestamp is in seconds) raw EEG signals (given in micro Volts) for all electrodes (AF3, F7, F3, FC5, T7, P7, O1, O2, P8, T8, FC6, F4, F8, AF4) are in the file (1). The timestamps (given in seconds) of displaying pictures, self-assessments of the emotional states (levels: sad, neutral, smiling) and the IAPS pictures ID are in the file (2). The display time of each picture is constant and equals 5 seconds. The low-resolution power of brainwaves (theta, alpha, low beta, high beta, and gamma) recorded for all electrodes during the session are in the file (3).

Dataset file

EEG_IAPS_session23_Kastrau_Jasik.zip
2.5 MB, S3 ETag 0c5215c90180ab8fe7d9f005df92913d-1, downloads: 67
The file hash is calculated from the formula
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
download file EEG_IAPS_session23_Kastrau_Jasik.zip

File details

License:
Creative Commons: by-nc-sa 4.0 open in new tab
CC BY-NC-SA
Non-commercial - Share-alike
Raw data:
Data contained in dataset was not processed.

Details

Year of publication:
2021
Verification date:
2021-08-04
Dataset language:
English
Fields of science:
  • biomedical engineering (Engineering and Technology)
  • physical sciences (Natural sciences)
DOI:
DOI ID 10.34808/4tje-5f64 open in new tab
Series:
Verified by:
Gdańsk University of Technology

Keywords

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