EDUCATION > Projects > Brian Computer Interface (BCI)

Brain Computer Interface (BCI)

Control a Robotic arm using brain signals (EEG) to play a chess game with computer

Project Lead

WhatsApp Image 2021-08-14 at 9.15.43 AM.jpg

Assoc. Prof. Dr. Eng. Amir R. Ali 

Executive Deputy


Eng. Malek Mahmoud 

Project Members


Engy Kassem, B.Sc. (2018)

Brief description for the project:

With the ingrowing technology, there is a huge potential in finding solutions to our daily problems. By the help of science and robotics, the potential is even doubled. Advanced technology is being discovered and used in our favor including brain signals. Nowadays, brain signals can be used to control various type of applications as well as being used as electrical signals and use them in our advanced projects which is a part of the aim of this project.

This project focuses on the idea of controlling a robot using brain signals to play a game. A robot is fabricated using specific materials that fits the requirements of the game chosen then the game is implemented virtually and simulated before simulating it on the robot. Then, the robot and brain signals are interfaced to achieve the required aim which is playing a game using only our brains.

WhatsApp Image 2021-08-30 at 8.14.34 PM (1).jpeg

Challenges of the project:

The control panel reads the brain waves and they translate it into actions, in the project’s case, it was translated into the mouse clicks in which how the game was initially designed. However, brain signals could have been used in a better way like using Cross correlation instead of the control panel. So, as for future work, it would be perfect if the brain signals were compared using cross correlation and not using the control panel. Cross correlation is a method similar to the convolution theorem where it compares two functions in the form of waveform, and returns the output using a specific function, cross correlation is not just a simple method, it can open gates for various applications. It makes many processes easier and it returns a very accurate output. The problem in using the cross correlation in this project lied in saving the brain waveform. It was easy to see or to stream the brain waves of the person wearing the helmet but these waves had to be saved in order to be used in another program like LabVIEW and compared to other waveform.