The CLAS (Cognitive Load, Affect and Stress) dataset was conceived as a freely accessible repository which is purposely developed to support research on the automated assessment of certain states of mind and the emotional condition of a person. 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. These and other related functionalities open additional opportunities in support of the advancement of research on (i) intelligent human-machine interfaces in entertainment, e-Health, e-Learning, e-Government and other applications; (ii) improving the efficiency of human-robot collaboration systems; (iii) risk assessment and management systems in robotics and in high-risk professions (rescue crews, military, miners etc.); and (iv) a wide range of personal applications aiming at the enhancement of health-related quality of life and wellbeing.
The CLAS dataset is a resource of labeled physiological recordings, which contain synchronized ECG, PPG, EDA and acclerometer signals captured while the test subjects are involved in some purposely designed interactive or perceptive task. Specifically, the interactive tasks are designed to evaluate different aspects of the momentary cognitive load, the degree of attention and concentration, or the cognitive capacity of a person. Specifically, in the interactive tasks the test subject is presented with a set of purposely designed mathematical and logical problems with the strict requirement for prompt response within a short time window.In the perceptive tasks, the test subjects are exposed to a series of carefully selected stimuli which aim to elicit emotions. In the perceptive tasks the test subjects typically receive instructions to simply watch the images or to follow the video clips. More details here.
Although the particular focus of our research is on the states of mind associated with negative emotions, mental strain and high cognitive effort, the CLAS dataset could offer an adequate support to research of a wider scope, such as general studies on attention assessment, cognitive load assessment, emotion recognition, as well as stress detection.
When using the CLAS dataset, please cite:
Markova, V., Ganchev, T., Kalinkov, K. (2019). CLAS: A Database for Cognitive Load, Affect and Stress Recognition, in Proceedings of the International Conference on Biomedical Innovations and Applications, (BIA-2019), art. no. 8967457, DOI: 10.1109/BIA48344.2019.8967457. Available on-line: https://ieeexplore.ieee.org/document/8967457
You can freely access a sample (PPG, ECG, EDA, Accelerometer) from here.
For receiving access to the whole CLAS dataset, please follow the procedure bellow:
1Compressed size - 2.03 GB, Uncompressed size - 13.9 GB, we recommend using 7-zip for extraction.