Author ORCID Identifier
Francesco N. Biondi : 0000-0002-5558-4707
Prarthana Pillai : 0000-0001-8875-3784
Prathamesh Ayare : 0000-0003-3631-6384
Balakumar Balasingam : 0000-0002-2669-7585
Document Type
Article
Publication Date
2020
Publication Title
Data in Brief
Volume
33
Keywords
Cognitive load detection;Eye-tracking;Pupil dilation;Human-computer interface;Detection response task (DRT);Psychological signals;Detection;Signal processing; Machine learning
Abstract
The dataset contains the following three measures that are widely used to determine cognitive load in humans: Detection Response Task - response time, pupil diameter, and eye gaze. These measures were recorded from 28 participants while they underwent tasks that are designed to permeate three different cognitive difficulty levels. The dataset will be useful to those researchers who seek to employ low cost, non-invasive sensors to detect cognitive load in humans and to develop algorithms for human-system automation. One such application is found in Advanced Driver Assistance Systems where eye-trackers are employed to monitor the alertness of the drivers. The dataset would also be helpful to researchers who are interested in employing machine learning algorithms to develop predictive models of humans for applications in human-machine system automation. The data is collected by the authors at the Department of Electrical & Computer Engineering in collaboration with the Faculty of Human Kinetics at the University of Windsor under the guidance of their Research Ethics Board.
DOI
10.1016/j.dib.2020.106389
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Pillai, Prarthana; Ayare, Prathamesh; Balasingam, Balakumar; Milne, Kevin; and biondi, Francesco. (2020). Response time and eye tracking datasets for activities demanding varying cognitive load. Data in Brief, 33.
https://scholar.uwindsor.ca/humankineticspub/46