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Electroencephalography and psychological assessment datasets to determine the efficacy of a low-cost, wearable neurotechnology intervention for reducing Post-Traumatic Stress Disorder symptom severity
- Source :
- Data in Brief, Vol 42, Iss , Pp 108066- (2022)
- Publication Year :
- 2022
- Publisher :
- Elsevier, 2022.
-
Abstract
- The datasets described here comprise electroencephalography (EEG) data and psychometric data freely available on data.mendeley.com. The EEG data is available in .mat formatted files containing the EEG signal values structured in two-dimensional (2D) matrices, with channel data and trigger information in rows, and samples in columns (having a sampling rate of 250Hz). Twenty-nine female survivors of the 1994 genocide against the Tutsi in Rwanda, underwent a psychological assessment before and after an intervention aimed at reducing Post-Traumatic Stress Disorder (PTSD) symptom severity. Three measures of trauma and four measures of wellbeing were assessed using empirically validated standardised assessments. The pre- and post- intervention psychometric data were analysed using non-parametric statistical methods and the post-intervention data were further evaluated according to diagnostic assessment rules to determine clinically relevant improvements for each group. The participants were assigned to a control group (CG, n = 9), a motor-imagery group (MI, n = 10), and a neurofeedback group (NF, n = 10). Participants in the latter two groups received Brain-Computer Interface (BCI) based training as a treatment intervention over a sixteen-day period, between the pre- and post- clinical interviews. The training involved presenting feedback visually via a videogame, based on real-time analysis of the EEG recorded data during the BCI-based treatment session. Participants were asked to regulate (NF) or intentionally modulate (MI) brain activity to affect/control the game.
Details
- Language :
- English
- ISSN :
- 23523409
- Volume :
- 42
- Issue :
- 108066-
- Database :
- Directory of Open Access Journals
- Journal :
- Data in Brief
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.3b2351af90074bc782c3909f6656d2d4
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.dib.2022.108066