A novel eye movement detection algorithm for EOG driven human computer interface

2010 ◽  
Vol 31 (9) ◽  
pp. 1041-1047 ◽  
Author(s):  
Zhao Lv ◽  
Xiao-pei Wu ◽  
Mi Li ◽  
Dexiang Zhang
Keyword(s):  
Eye Movement ◽  
Detection Algorithm ◽  
Computer Interface ◽  
Human Computer Interface ◽  
Movement Detection

Eye-Voice-Controlled Interface

1986 ◽  
Vol 30 (4) ◽  
pp. 322-326 ◽  
Author(s):  
Floyd A. Glenn ◽  
Helene P. Iavecchia ◽  
Lorna V. Ross ◽  
James M. Stokes ◽  
William J. Weiland ◽  
...  
Keyword(s):  
Eye Movement ◽  
Computer Interface ◽  
Human Computer Interface ◽  
Interface System ◽  
Technical Issues ◽  
Processing Algorithms ◽  
Feedback Techniques

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.

scholarly journals Development of an Eye Tracking-Based Human-Computer Interface for Real-Time Applications

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3630 ◽  
Author(s):  
Radu Gabriel Bozomitu ◽  
Alexandru Păsărică ◽  
Daniela Tărniceriu ◽  
Cristian Rotariu
Keyword(s):  
Eye Tracking ◽  
Real Time ◽  
Detection Rate ◽  
Detection Algorithm ◽  
Computer Interface ◽  
Human Computer Interface ◽  
Detection Techniques ◽  
Scene Image ◽  
Real Time Applications ◽  
Circular Target

In this paper, the development of an eye-tracking-based human–computer interface for real-time applications is presented. To identify the most appropriate pupil detection algorithm for the proposed interface, we analyzed the performance of eight algorithms, six of which we developed based on the most representative pupil center detection techniques. The accuracy of each algorithm was evaluated for different eye images from four representative databases and for video eye images using a new testing protocol for a scene image. For all video recordings, we determined the detection rate within a circular target 50-pixel area placed in different positions in the scene image, cursor controllability and stability on the user screen, and running time. The experimental results for a set of 30 subjects show a detection rate over 84% at 50 pixels for all proposed algorithms, and the best result (91.39%) was obtained with the circular Hough transform approach. Finally, this algorithm was implemented in the proposed interface to develop an eye typing application based on a virtual keyboard. The mean typing speed of the subjects who tested the system was higher than 20 characters per minute.

scholarly journals FPGA Implementation of Eye Movement Detection Algorithm

2021 ◽  
Author(s):  
KISHORE KUMAR GUNDUGONTI ◽  
Balaji Narayanam
Keyword(s):  
Eye Movement ◽  
Haar Wavelet ◽  
Detection Algorithm ◽  
Hardware Architecture ◽  
Simulation Tool ◽  
Movement Detection ◽  
Haar Wavelet Transform ◽  
System Generator ◽  
Reading Activity ◽  
Left Movement

Abstract In this paper, we propose an simple and efficient VLSI hardware architecture is implemented for eye movement detection. For Eye movement detection reading activity Electrooculography (EOG) signal is considered. Here, for denoising the noisy EOG signal efficient FIR filter and for decomposition of denoised EOG signal an efficient Haar wavelet transform architecture is used respectively. The modified VLSI hardware architecture method detected the saccade (left movement of eye and right movement of eye) and blink efficiently. The hardware architecture of the eye movement detection algorithm functionality is verified by using Xilinx System Generator hardware co-simulation tool. The eye movement detection algorithm is implemented on the ZedBoard FPGA using Xilinx Vivado design suite.

scholarly journals Human-Computer Interface with Eye Movement

2020 ◽  
Vol 9 (7) ◽  
pp. 920-924
Keyword(s):  
Eye Movement ◽  
High Precision ◽  
Eye Contact ◽  
Human Machine Interface ◽  
Computer Interface ◽  
Human Computer Interface ◽  
Lightweight Construction ◽  
Actual Usage ◽  
Mouse Pointer ◽  
Machine Interface

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.

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