Power of the SMR brainwaves in the mental imagery experiment in sport: the "Training Session" scenario. - Open Research Data - Bridge of Knowledge

Search

Power of the SMR brainwaves in the mental imagery experiment in sport: the "Training Session" scenario.

Description

The data were collected to perform research on the neural oscillation during mental imagery in sport. The study's main aim was to examine the cortical correlations of imagery depending on instructional modality (guided vs self-produced) using various sport-related scripts. The research was based on the EEG signals recorded during the session with the experienced Olympic sailor athlete. The raw electroencephalographic data were collected using the 32-channels (incl. ground and reference) g. Nautilus wearable EEG headset with 24-bit ADC accuracy at 250 Hz sampling rate. All signals were properly preprocessed to remove any artifacts and filter unnecessary frequencies. At the processing stage, the Fast Fourier Transform (FFT) with Kaiser windowing, bandpass filters, and the inverse FFT were applied to obtain the pure SMR brainwaves. Finally, the power of the SMR brainwaves was calculated.

The dataset is arranged in 30 columns. Each column corresponds to one EEG electrode. The first 37 seconds (i.e. 9250 samples) of the SMR brainwaves' power are related to the guided imagery part of the "Training Session" situation. Then, there is 2 seconds break (500 samples), after which the self-produced imagery part of the "Training Session" situation is presented with a duration of 60 seconds (i.e. 15000 samples).

Dataset file

Training_Session_all_electrodes_power_SMR.csv
13.9 MB, S3 ETag c4eafa9f6f6ce913051fe1cb79d04a8f-1, downloads: 57
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

File details

License:
Creative Commons: by-nc-sa 4.0 open in new tab
CC BY-NC-SA
Non-commercial - Share-alike

Details

Year of publication:
2021
Verification date:
2021-04-28
Dataset language:
English
Fields of science:
  • psychology (Social studies)
  • biomedical engineering (Engineering and Technology)
  • health sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/fy6v-rj30 open in new tab
Series:
Verified by:
Gdańsk University of Technology

Keywords

Cite as

Authors

seen 103 times