Robust Eye Movement Recognition Using EOG Signal for Human-Computer Interface

Author(s):  
Siriwadee Aungsakun ◽  
Angkoon Phinyomark ◽  
Pornchai Phukpattaranont ◽  
Chusak Limsakul
1986 ◽  
Vol 30 (4) ◽  
pp. 322-326 ◽  
Author(s):  
Floyd A. Glenn ◽  
Helene P. Iavecchia ◽  
Lorna V. Ross ◽  
James M. Stokes ◽  
William J. Weiland ◽  
...  

The Ocular Attention-Sensing Interface System (OASIS) is an innovative human-computer interface which utilizes eye movement and voice commands to communicate messages between the operator and the system. This report initially describes some technical issues relevant to the development of such an interface. The results of preliminary experiments which evaluate alternative eye processing algorithms and feedback techniques are presented. Candidate interface applications are also discussed.


This paper focuses on using IR handset to operate the PC's mouse pointer, which distinguishes the client's eyeball creation for Human Machine Interface. Having the ability to perform left, right, up, down and double taps based on different eye squints with significantly high precision, it uses a viable example classification calculation. In view of the actual usage of Eye Contact, the sensor projections are usually used to gage selflook headings in low- minus- calculations. The proposed architecture is a promising human-PC interface for flexible eye following applications due to its lightweight construction and strong precision.


2021 ◽  
Vol 3 (4) ◽  
pp. 336-346
Author(s):  
Judy Simon

Human Computer Interface (HCI) requires proper coordination and definition of features that serve as input to the system. The parameters of a saccadic and smooth eye movement tracking are observed and a comparison is drawn for HCI. This methodology is further incorporated with Pupil, OpenCV and Microsoft Visual Studio for image processing to identify the position of the pupil and observe the pupil movement direction in real-time. Once the direction is identified, it is possible to determine the accurate cruise position which moves towards the target. To quantify the differences between the step-change tracking of saccadic eye movement and incremental tracking of smooth eye movement, the test was conducted on two users. With the help of incremental tracking of smooth eye movement, an accuracy of 90% is achieved. It is found that the incremental tracking requires an average time of 7.21s while the time for step change tracking is just 2.82s. Based on the observations, it is determined that, when compared to the saccadic eye movement tracking, the smooth eye movement tracking is over four times more accurate. Therefore, the smooth eye tracking was found to be more accurate, precise, reliable, and predictable to use with the mouse cursor than the saccadic eye movement tracking.


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