Group: 2014-FYP-21



Mr. Arsalan A Rahim


Human Brain operates by the interconnection of billions of neurons. Every activity/thought result in an electrical charge in brain. This electric charge is transmitted by the extensive network of neurons and activities/functions are performed on cellular level. Every single operation in the body is commanded by the brain in the form of electric signals/waves. Different thoughts result in different kind of waves, varying in amplitude and frequency. These signals, also known as EEG signals, are in the range of micro-volts. If we obtain these signals and process them, different activities can be performed on the basis of distinguished signals. In our project, we are aiming to control a quadcopter using EEG signals. In order to acquire EEG signals weve developed a portable EEG board that fetches the brain signals through different electrodes placed on the scalp of a person. This board is not only portable but also low cost as compared to other commercial headsets, and gives similar quality results. The acquired raw EEG signals are then amplified, filtered and converted into digital signals through an analog-to-digital convertor. Distinguishing features, such as power spectral density and FFT, are extracted from purified signals using a microcontroller i.e. RaspberryPi. After this, machine learning algorithms are applied to classify the signals on the basis of these features. Thus, signals are classified into left, right, forward, backward, up and down. On the basis of these classified signals, PWM signals are generated through RaspberryPi and applied to the potentiometers present in the remote control of quadcopter. The remote control transmits signals to the controller of quadcopter and hence the flight of quadcopter is controlled. Thus, the flight of the quadcopter can be controlled by EEG signals. Quadcopter flight control is one application of EEG signals. This method of EEG signal acquisition and processing can be used for various purposes. For example, diagnosis of brain related diseases such as, epilepsy, Alzheimers disease, seizure disorder, dementia, seizure, etc. Another application of EEG signals is operating machines/robots. This application is particularly useful for disabled and paralyzed individuals. We have operated an electronic wheelchair and a robotic arm using EEG signals. So using this technology, any type of action can be performed by mere thoughts.

Second Link:

Download Link

Thesis Report:

Download Link


Team Members:

Facebook Page


Our Vision

To ensure understanding and application of engineering fundamentals to address social needs.

Our Mission

To become a center of excellence in knowledge creation and dissemination by inculcating analysis and design skills in electrical engineering students.


Please provide us your email address to subscribe Newsletter of UET Lahore issued bi-annually.