EEG-based brain–computer interfaces. (December 2017) - McFarland, D.J.; Wolpaw, J.R.
Abstract: Brain–Computer Interfaces (BCIs) are real-time computer-based systems that translate brain signals into useful commands. To date most applications have been demonstrations of proof-of-principle; widespread use by people who could benefit from this technology requires further development. Improvements in current EEG recording technology are needed. Better sensors would be easier to apply, more confortable for the user, and produce higher quality and more stable signals. Although considerable effort has been devoted to evaluating classifiers using public datasets, more attention to real-time signal processing issues and to optimizing the mutually adaptive interaction between the brain and the BCI are essential for improving BCI performance. Further development of applications is also needed, particularly applications of BCI technology to rehabilitation. The design of rehabilitation applications hinges on the nature of BCI control and how it might be used to induce and guide beneficial plasticity in the brain. Highlights: Most EEG-based BCIs use P300 evoked potentials, sensorimotor rhythms, or the steady-state evoked potentials. Improved recording and signal processing are needed to increase BCI practicality. Online evaluation of algorithms is essential because it takes into account ongoing adaptive interactions. BCIs show promise as new methods for enhancing functional recovery for people with chronic disorders.