Artificial Intelligence
A low-cost interface for control of computer functions by means of eye movements
Computers in Biology and Medicine
Nessi: an EEG-controlled web browser for severely paralyzed patients
Computational Intelligence and Neuroscience - Brain-Computer Interfaces: Towards Practical Implementations and Potential Applications
Brain-Robot Interface for Controlling a Remote Robot Arm
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part II: Bioinspired Applications in Artificial and Natural Computation
Ensemble SWLDA Classifiers for the P300 Speller
Proceedings of the 13th International Conference on Human-Computer Interaction. Part II: Novel Interaction Methods and Techniques
IEEE Transactions on Robotics - Special issue on rehabilitation robotics
EOG-based Human-Computer Interface system development
Expert Systems with Applications: An International Journal
Development of an expert multitask gadget controlled by voluntary eye movements
Expert Systems with Applications: An International Journal
Mental tasks-based brain-robot interface
Robotics and Autonomous Systems
A local neural classifier for the recognition of EEG patterns associated to mental tasks
IEEE Transactions on Neural Networks
Assistive robot application based on an RFID control architecture and a wireless EOG interface
Robotics and Autonomous Systems
Expert Systems with Applications: An International Journal
Internet browsing application based on electrooculography for disabled people
Expert Systems with Applications: An International Journal
Endogenous brain-machine interface based on the correlation of EEG maps
Computer Methods and Programs in Biomedicine
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This paper describes a brain-computer interface (BCI) based on electroencephalography (EEG) that has been developed to assist disabled people. The BCI uses the evoked potentials paradigm (through P300 and N2PC waves detection), registering the EEG signals with 16 electrodes over the scalp. Three applications have been developed using this BCI paradigm. The first application is an Internet browser that allows to access to Internet and to control a computer. The second application allows controlling a robotic arm in order to manipulate objects. The third application is a basic communication tool that allows severe disabled people to interact with other people using basic commands related to emotions and needs. All the applications are composed by visual interfaces that show different options related to the application. These options are pseudo-randomly flickering in a screen. In order to select a specific command, the user must focus on the desired option. The BCI is able to obtain the desired option by detecting the P300 and N2PC waves produced as an automatic response of the brain to attended visual stimuli and finally classifying these signals. Different experiments with volunteers have been carried out in order to validate the applications. The experimental results obtained as well as the improvement achieved by using both types of evoked potentials are shown in the paper.