Document Type
Review
Publication Date
6-21-2012
Description
A brain-computer interface (BCI) enables communication without movement based on brain signals measured with electroencephalography (EEG). BCIs usually rely on one of three types of signals: the P300 and other components of the event-related potential (ERP), steady state visual evoked potential (SSVEP), or event related desynchronization (ERD). Although P300 BCIs were introduced over twenty years ago, the past few years have seen a strong increase in P300 BCI research. This closed-loop BCI approach relies on the P300 and other components of the event-related potential (ERP), based on an oddball paradigm presented to the subject. In this paper, we overview the current status of P300 BCI technology, and then discuss new directions: paradigms for eliciting P300s; signal processing methods; applications; and hybrid BCIs. We conclude that P300 BCIs are quite promising, as several emerging directions have not yet been fully explored and could lead to improvements in bit rate, reliability, usability, and flexibility.
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.
Citation Information
Fazel-Rezai, Reza; Allison, Brendan Z.; Guger, Christoph; Sellers, Eric W.; Kleih, Sonja C.; and Kübler, Andrea. 2012. P300 Brain Computer Interface: Current Challenges and Emerging Trends. Frontiers in Neuroengineering. (JUNE). 1-30. https://doi.org/10.3389/fneng.2012.00014 ISSN: 1662-6443
Copyright Statement
Copyright © 2012 Fazel-Rezai, Allison, Guger, Sellers, Kleih and Kübler. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third- party graphics etc.