CogBeacon

CogBeacon: A Multi-Modal Dataset for Modeling Cognitive Fatigue

Overview

CogBeacon is a multi-modal dataset designed to assess cognitive fatigue in human performance. It includes 76 sessions from 19 users performing the Wisconsin Card Sorting Test (WCST), a cognitive test that evaluates cognitive flexibility and reasoning. Data collected during these sessions include EEG functionality, facial keypoints, real-time self-reports on cognitive fatigue, and performance metrics.

Dataset Structure

The dataset is organized into four main folders:

1. EEG Data:

   • Filename Structure: Each session is stored in a separate folder named "user_ _ _ ".
   • Data Types: Raw EEG, Absolute Frequency Bands, Relative Frequency Bands, Session Score for each Frequency band, Signal Quality Indicator.
   • Equipment: Data recorded using the Muse EEG headset.

2. Facial Keypoints:

   • Filename Structure: Data stored in the "face_keypoints" folder, with filenames structured as <round_under_the_same_rule> _ _ .
   • Data Collection: Captured using a webcam at 2 FPS, employing a Regression Tree approach for keypoint identification.

3. Fatigue Self Report:

   • Filename Structure: Data stored in the "fatigue_self_report" folder as CSV files, with filenames following the same structure as other data types.
   • Data Content: Records the total number of times a user pressed a button to indicate cognitive fatigue.

4. User Performance:

   • Filename Structure: Data stored as CSV files in the "user_performance" folder, with filenames structured similarly to other data types.
   • Metrics Included: Round Number, Question Number, Level, Score, Stimuli, Stimuli Type, Response, Time, Correct, NON-PER Errors, PER Errors.

Additional Resources

• Machine Learning Analysis: Code and data used for the ML analysis can be found HERE.
• EEG Data Codes: Python codes for EEG data processing are available HERE.

Confidentiality & Data Sharing

The dataset was approved by the Institutional Review Board (IRB) of the University of Texas at Arlington. For inquiries regarding confidentiality or data sharing, contact the IRB office at UTA or the project personnel.