Contact-Free Cognitive Load Recognition Based on Eye Movement
Joint Authors
Liu, Xin
Chen, Tong
Xie, Guoqiang
Liu, Guangyuan
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-11-30
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
The cognitive overload not only affects the physical and mental diseases, but also affects the work efficiency and safety.
Hence, the research of measuring cognitive load has been an important part of cognitive load theory.
In this paper, we proposed a method to identify the state of cognitive load by using eye movement data in a noncontact manner.
We designed a visual experiment to elicit human’s cognitive load as high and low state in two light intense environments and recorded the eye movement data in this whole process.
Twelve salient features of the eye movement were selected by using statistic test.
Algorithms for processing some features are proposed for increasing the recognition rate.
Finally we used the support vector machine (SVM) to classify high and low cognitive load.
The experimental results show that the method can achieve 90.25% accuracy in light controlled condition.
American Psychological Association (APA)
Liu, Xin& Chen, Tong& Xie, Guoqiang& Liu, Guangyuan. 2016. Contact-Free Cognitive Load Recognition Based on Eye Movement. Journal of Electrical and Computer Engineering،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1108406
Modern Language Association (MLA)
Liu, Xin…[et al.]. Contact-Free Cognitive Load Recognition Based on Eye Movement. Journal of Electrical and Computer Engineering No. 2016 (2016), pp.1-8.
https://search.emarefa.net/detail/BIM-1108406
American Medical Association (AMA)
Liu, Xin& Chen, Tong& Xie, Guoqiang& Liu, Guangyuan. Contact-Free Cognitive Load Recognition Based on Eye Movement. Journal of Electrical and Computer Engineering. 2016. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1108406
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1108406