Multi-channel Wireless EEG Recordings of Young Adults for Anxiety Screening based on GAD-7
Description
The EEG was recorded using a wireless EMOTIV EPOC+ headset (with 14 channels and a sampling rate of 128 Hz) from 38 young adults (aged between 18 and 25 years). Before EEG acquisition, after taking participant consent, a self-reported survey following the GAD-7 questionnaire was filled out by the participants to find the ground truth for screening anxiety. There were 23 participants found to have GAD-7 scores more than or equal to 15 classified as Anxiety (labelled as ASub1-ASub23), while 15 participants had GAD-7 scores less than or equal to 4 classified as Anxiety Control subjects (labelled as ACSub1-ACSub15). Each recording was 5 minutes long for each participant. The 14 EEG channels are placed according to the International 10-20 electrode montage system: eight frontal electrodes (AF3, F3, F7, FC5, AF4, F4, F8 and FC6), two temporal electrodes (T7 and T8), two parietal electrodes (P7 and P8), two occipital electrodes (O1 and O2), and two reference channels (P3 and P4). The dataset has .mat file extension (can be opened by MATLAB software). Each file has a data size of 38,400 x 14, where each column denotes channel number and each row denotes sample number. Since each recording is 5 minutes long (300 seconds), each channel has 38,400 samples, which is equivalent to 300 seconds (sampling rate of 128 Hz). The ethical approval through the Institutional Review Board (IRB) of the Independent University, Bangladesh (IUB) was taken prior to the experiment. All the participants were students of IUB, whose EEG recordings were conducted at the Biomedical Instrumentation and Signal Processing Lab (BISPL) of the Department of Electrical and Electronic Engineering (EEE), IUB.
Files
Steps to reproduce
EEG Electrode Montage: International 10-20 System EEG Recording Headset: Emotiv EPOC+ Software to Analyse and Process Raw EEG: MATLAB Anxiety Screening Tool: GAD-7 For details, please follow the methods section of the following articles to reproduce and cite them accordingly. 1) Sakib, Nazmus, Tasnuva Faruk, and Md Kafiul Islam. "Wireless EEG based anxiety screening among young adults using machine learning model." In Proceedings of the 2023 8th International Conference on Biomedical Imaging, Signal Processing, pp. 97-103. 2023. 2) N. Sakib, K. Islam and T. Faruk, "Effect of Artifact Removal in Machine Learning Based Anxiety Screening Using EEG Signal," 2025 4th International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST), Dhaka, Bangladesh, 2025, pp. 498-503, doi: 10.1109/ICREST63960.2025.10914438.
Institutions
- Independent University