Honors College Theses

Publication Date

5-2-2023

Major

Electrical Engineering (B.S.)

Document Type and Release Option

Thesis (open access)

Faculty Mentor

Rocio Alba-Flores

Abstract

A drone, also known as an unmanned aerial vehicle (UAV), is a type of aircraft that is operated remotely or autonomously. The utilization of drones increased because it is now possible to use them to perform tasks that would be too complicated for human beings to do. Electroencephalograms (EEG) are generated by the electrical activity of the brain and can be measured by placing electrodes on the scalp. The idea of controlling drones using EEG signals refers to the use of EEG technology to control the movement of a drone. EEG signals are used to determine the user's intention and translate that into commands that are sent to the drone.For this project, we developed and tested a system that has the purpose to control a drone using a headband that detects EEG signals from the drone’s pilot when he/she performs facial gestures. A commercial EEG headband will be used to record the EEG signals generated when three facial gestures are performed: raise eyebrows, hard blink, and look left. The headband has three electrodes in the form of small metal disks that allow three frontal cortex measurements. For this experiment, the recordings will be taken from three different people and the EEG signals recorded from them will be analyzed and recorded using the OpenBCI GUI software. The data recorded will be transferred to MATLAB software. Then the data will go through a feature extraction process, to design an Artificial Neural Network (ANN). After that, the Artificial Neural Network will be trained to classify the facial gesture selected for the experiment and once its training is completed the Neural network will be converted into a function that will be sent to MATLAB for the purpose to send commands DJI Tello drone based on the classification analysis performed by the Neural Network created.

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