Brain-computer interface communication and control using EEG signals - Marco, Eliezer A. (2007)
Recent studies in the field of biomedical engineering have introduced the possibility that a person's electroencephalographic activity or any other measure of brain activity can be used as an alternative communication channel for sending messages and commands to the external world. Instead of using the normal pathways of nerves and muscles, a person with the aid of a computer could directly use his or her thoughts to operate simple electronic devices, manipulate word processing programs, navigate a mobile robot, or even control prosthetic arms and limbs. As it generally termed, this Brain-Computer Interface (BCI) would be an extremely valuable nugmentative technology for people with severe neuromuscular disorders and motor function disabilities. In line with the continuing development of this technology, this project aims to design a BCI system wherein a person could control the switching of three different LEDs by performing two predetermined mental tasks. The person's brain activity will first be recorded using electroencephalograph (EEG) signals. The signals will be amplified to a suitable voltage level and the necessary signal characteristics will be extracted using MATLAB. The system then will use a Neural Networks classifier to determine which mental task is being performed. Finally, depending on the mental task, the corresponding LED will be switched on. For further applications, the LEDs could represent more advanced operations such as the commands controlling the navigation of a wheelchair or the selection of options in a simple computer program.