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Power of the low alpha brainwaves in the mental imagery experiment in sport: the "Slow Start" scenario.
Description
The data were collected to perform research on the neural oscillation during mental imagery in sport. The main aim of the study was to examine the cortical correlates 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 low alpha brainwaves. Finally, the power of the low alpha brainwaves was calculated.
The dataset is arranged in 30 columns. Each column corresponds to one EEG electrode. The first 47 seconds (i.e. 11750 samples) of the power of the low alpha brainwaves are related to the guided imagery part of the "Slow Start" situation. Then, there is 2 seconds break (500 samples), after which the self-produced imagery part of the "Slow Start" situation is presented with a duration of 60 seconds (i.e. 15000 samples).
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 BY-NC-SANon-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 10.34808/2qf3-aj73 open in new tab
- Series:
- Verified by:
- Gdańsk University of Technology
Keywords
- EEG
- flow state
- attentional focus
- neural efficiency
- transient hypofrontality hypothesis
- athlete
- mental imagery
- neural oscillation
- biosignal processing
- low alpha brainwaves
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