Eye Tracking Based Control System for Natural Human-Computer Interaction

Joint Authors

Yuan, Shyan-Ming
Liu, Xiaolong
Zhang, Xuebai
Lin, Shu-Fan

Source

Computational Intelligence and Neuroscience

Issue

Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-9, 9 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2017-12-18

Country of Publication

Egypt

No. of Pages

9

Main Subjects

Biology

Abstract EN

Eye movement can be regarded as a pivotal real-time input medium for human-computer communication, which is especially important for people with physical disability.

In order to improve the reliability, mobility, and usability of eye tracking technique in user-computer dialogue, a novel eye control system with integrating both mouse and keyboard functions is proposed in this paper.

The proposed system focuses on providing a simple and convenient interactive mode by only using user’s eye.

The usage flow of the proposed system is designed to perfectly follow human natural habits.

Additionally, a magnifier module is proposed to allow the accurate operation.

In the experiment, two interactive tasks with different difficulty (searching article and browsing multimedia web) were done to compare the proposed eye control tool with an existing system.

The Technology Acceptance Model (TAM) measures are used to evaluate the perceived effectiveness of our system.

It is demonstrated that the proposed system is very effective with regard to usability and interface design.

American Psychological Association (APA)

Zhang, Xuebai& Liu, Xiaolong& Yuan, Shyan-Ming& Lin, Shu-Fan. 2017. Eye Tracking Based Control System for Natural Human-Computer Interaction. Computational Intelligence and Neuroscience،Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1141018

Modern Language Association (MLA)

Zhang, Xuebai…[et al.]. Eye Tracking Based Control System for Natural Human-Computer Interaction. Computational Intelligence and Neuroscience No. 2017 (2017), pp.1-9.
https://search.emarefa.net/detail/BIM-1141018

American Medical Association (AMA)

Zhang, Xuebai& Liu, Xiaolong& Yuan, Shyan-Ming& Lin, Shu-Fan. Eye Tracking Based Control System for Natural Human-Computer Interaction. Computational Intelligence and Neuroscience. 2017. Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1141018

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1141018