Edinburgh Napier University

  Rapid development in highly parallel neurophysiological recording techniques along with sophisticated signal processing tools allow direct communication with neuronal processes at different levels. One important level from the point of view of Rehabilitation Engineering & Assistive Technology is to use the Electroencephalogram (EEG) signals to interface with assistive devices. This type of brain-computer interface (BCI) aims to reestablish the broken loop of the persons with motor dysfunction(s). However, with the growing availability of of instruments and processes for implementation, the BCI is also getting more complex. In this work, the authors present a model for reduced complexity BCI based on EEG signals through a few simple processes for automated navigation and control of robotic device. It is demonstrated that not only with few number of electrodes, but also using simple features like evoked responses caused by Saccadic eye movement can be used in building robust BCI for rehabilitation which may revolutionize the development of assitive devices for the disabled.