Response time and eye tracking datasets for activities demanding varying cognitive load
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 differ...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2020-12-01
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| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340920312683 |
| _version_ | 1818391762246303744 |
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| author | Prarthana Pillai Prathamesh Ayare Balakumar Balasingam Kevin Milne Francesco Biondi |
| author_facet | Prarthana Pillai Prathamesh Ayare Balakumar Balasingam Kevin Milne Francesco Biondi |
| author_sort | Prarthana Pillai |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-14T05:18:40Z |
| format | Article |
| id | doaj.art-8ec572ca73074597a8492d2db8d68722 |
| institution | Directory Open Access Journal |
| issn | 2352-3409 |
| language | English |
| last_indexed | 2024-12-14T05:18:40Z |
| publishDate | 2020-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj.art-8ec572ca73074597a8492d2db8d687222022-12-21T23:15:44ZengElsevierData in Brief2352-34092020-12-0133106389Response time and eye tracking datasets for activities demanding varying cognitive loadPrarthana Pillai0Prathamesh Ayare1Balakumar Balasingam2Kevin Milne3Francesco Biondi4Department of Electrical and Computer Engineering, University of Windsor, 401 Sunset Avenue, Windsor, ON, N9G 3P4, Canada; Corresponding author.Department of Electrical and Computer Engineering, University of Windsor, 401 Sunset Avenue, Windsor, ON, N9G 3P4, CanadaDepartment of Electrical and Computer Engineering, University of Windsor, 401 Sunset Avenue, Windsor, ON, N9G 3P4, CanadaFaculty of Human Kinetics, University of Windsor, 401 Sunset Avenue, Windsor, ON N9G 3P4, CanadaFaculty of Human Kinetics, University of Windsor, 401 Sunset Avenue, Windsor, ON N9G 3P4, CanadaThe 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.http://www.sciencedirect.com/science/article/pii/S2352340920312683Cognitive load detectionEye-trackingPupil dilationHuman-computer interfaceDetection response task (DRT)Psychological signals |
| spellingShingle | Prarthana Pillai Prathamesh Ayare Balakumar Balasingam Kevin Milne Francesco Biondi Response time and eye tracking datasets for activities demanding varying cognitive load Data in Brief Cognitive load detection Eye-tracking Pupil dilation Human-computer interface Detection response task (DRT) Psychological signals |
| title | Response time and eye tracking datasets for activities demanding varying cognitive load |
| title_full | Response time and eye tracking datasets for activities demanding varying cognitive load |
| title_fullStr | Response time and eye tracking datasets for activities demanding varying cognitive load |
| title_full_unstemmed | Response time and eye tracking datasets for activities demanding varying cognitive load |
| title_short | Response time and eye tracking datasets for activities demanding varying cognitive load |
| title_sort | response time and eye tracking datasets for activities demanding varying cognitive load |
| topic | Cognitive load detection Eye-tracking Pupil dilation Human-computer interface Detection response task (DRT) Psychological signals |
| url | http://www.sciencedirect.com/science/article/pii/S2352340920312683 |
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