The CLAS (Cognitive Load, Affect and Stress) dataset was conceived as a freely-accessible repository purposely developed to support research on the automated assessment of certain states of mind and a person's emotional condition. This resource is intended to support RTD activities aiming at the development of intelligent human-computer interaction (HCI) interfaces that incorporate functionalities allowing for the automated recognition of human emotions, the automated detection of stress conditions, the automated assessment of the degree of concentration, cognitive load, and momentary cognitive capacity, and can account for some personality traits related to the ability to quickly solve logical and mathematical problems under strict time constraints.
The CLAS dataset is available through the IEEEDataPort repository: link
Please, cite this dataset as follows:
V. Markova, T. Ganchev and K. Kalinkov, "CLAS: A Database for Cognitive Load, Affect and Stress Recognition," 2019 International Conference on Biomedical Innovations and Applications (BIA), 2019, pp. 1-4, doi: https://doi.org/10.1109/BIA48344.2019.8967457.