Design and Implementation of Electrooculogram EOG Based Prototype System


  1. Reema Althabit
  2. Hussah Alateeq
  3. Fatimah Alfilfil
  4. Atheer Alhamadi
  5. Supervised by Engr.Kamran Hameed


Biomedical Engineering


Imam Abdulrahman bin Faisal university


The idea of this project was obtained after observing some cases of paralyzed patients who are suffering to do their simple daily activities and adapt to their situation. Paralyzed patients lose the ability to move their muscles, however their eyes performance is not affected. We are designing an Electrooculogram (EOG) based system to give them some control in their environment and enhance their self-independency. Electrooculography is a technique used to estimate the eyeball movement. Based on the eye movements, various EOG wave patterns will be produced, measurements are based on cornea-retinal electrical potential difference. The strength of the EOG signal is weak since it ranges from 10 - 200 μV, which makes it very difficult to be acquired and processed.

Summary of Work

The general method followed in this project consists of two modules, acquisition module and signal-processing module. The formation of the acquisition module consists of bio-potential surface electrodes, and the EOG circuit. After EOG signal is acquired, it will be processed using Arduino software and hardware

Block Diagram of The Overall System

Designed EOG Circuit 


The expected outcome is that by connecting the acquired signal to the Arduino, the Arduino will be able to process the signal. Depending on the eyeball movement there will be four different signal types. Each one will express a particular order based on the eyeball direction. 


Project Schematic Diagram

Summary of Results

The EOG circuit is designed with different stages of amplifying and filtering in order to convert the weak signal, which is in the microvolt range to have a final usable signal in the volt rang. 


Input EOG Signal 

Output EOG Signal 

Output EOG signal For Left And Right movements

Output EOG Signal for 5 Times Blinking

Arduino output for four led prototype

Take-home Messages

Empower people with disabilities


D'Souza, Sandra, and N. Sriraam

            2014    Design of EOG Signal Acquisition System Using Virtual Instrumentation. International Journal of Measurement Technologies and Instrumentation Engineering 4(1):1-16.

Gupta, S. Sen, et al.

            2012    Detecting eye movements in EEG for controlling devices. 2012 IEEE International Conference on Computational Intelligence and Cybernetics (CyberneticsCom), 2012, pp. 69-73.

Hegde, V. N., R. S. Ullagaddimath, and S. Kumuda

            2016    Low cost eye based human computer interface system (Eye controlled mouse). 2016 IEEE Annual India Conference (INDICON), 2016, pp. 1-6.

Kim, Myoung Ro, and Gilwon Yoon

            2013    Control Signal from EOG Analysis and Its Application. International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering 7.

Summary of Work
Summary of Results
Take-home Messages
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