EEG-Dataset-for-Psychosocial-Stress-TSST-with-Personality-Labels

This dataset contains high-resolution electroencephalography (EEG) recordings from 19 participants undergoing the Trier Social Stress Test (TSST), a widely used protocol for inducing psychosocial stress in experimental settings. Each subject participated in four distinct phases: baseline (resting state), mental arithmetic task, mock job interview, and recovery.EEG was recorded using a 64-channel system at 1024 Hz sampling rate with 24-bit resolution, offering fine-grained temporal and spatial information on brain activity. In addition to raw EEG data, the dataset includes:Precomputed power spectral density (PSD) features across five canonical bands (Delta, Theta, Alpha, Beta, and Gamma)Personality trait labels based on the Big Five model (extracted from validated psychometric questionnaires)Feature matrices (76 segments \u00d7 320 features per file) designed for machine learning applicationsThis dataset is ideal for researchers studying stress-related neural dynamics, personality-neurophysiological interactions, EEG-based biometric modeling, and other affective computing tasks. The comprehensive structure supports both traditional statistical analyses and deep learning pipelines.All data is anonymized and formatted for reproducibility, adhering to open science practices. If anyone need RAW dataset , it may be provided upon the request.