NON-INVASIVE BRAIN EEG ROBOT NAVIGATION FRAMEWORK BASED ON EMOTIV EPOC

• Main Author: Soffar, Hossam El-Sayed Mohamed Soffar
• Format: Final Year Project
• Language: English
• Published: Universiti Teknologi Petronas 2013
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://utpedia.utp.edu.my/9487/1/Hossam%20soffar_Final%20Report_12286.pdf; http://utpedia.utp.edu.my/9487/
• Institution: Universiti Teknologi Petronas

A Brain computer interface (BCI) has introduced new dimensions and created a new era for creative applications for developers and researchers giving alternative communication channels for people suffering of motor disabilities. The motor system is currently the primary focus, where EEG signals are being obtained while the subject is imagining or performing a motor response. With the help of an EEG signals, navigating a robot or controlling a wheel chair has come from science fiction movies or stories to reality. The purpose of this study is to design a navigation framework for a robot or a wheel chair using the capabilities of the brain EEG using an online acquisition device in our case it’s Emotiv Epoc. The framework is based on SSVEP focusing on visual cortex EEG signal analysis, the methodology used to complete this application is agile software development which basically is based on iterative and incremental development providing a rapid and flexible product. The tools used to implement the framework are divided into two categories hardware and software as for the hardware EEG acquisition device is used to acquire EEG signals, a robot based on NXT logo is used to demonstrate the control capabilities of the framework, as for the software Emotiv SDK , Open vibe as a signal processing and visual studio to design the a GUI as a man in the middle for interfacing the EEG signal processing platform with the robot.