Lets play Tic-Tac-Toe: A Brain-Computer Interface case study in cerebral palsy

Operating Brain-Computer Interfaces (BCIs) that are based on the detection of changes in oscillatory noninvasive electroencephalogram (EEG) typically involves learning. Commonly the learning process is distributed between the user
(reliable EEG pattern generation) and the machine (robust EEG pattern detection). Standard training approaches, however, typically do not allow users to gain meaningful levels of control. A better understanding of brain functioning or the use of sophisticated machine learning are ways to enhance control. Rethinking training paradigms is another option. In this paper, we enhance our game-based training approach by adding competitive elements. Winning is a powerful motivator that increases user engagement of the typically boring BCI training experience. We report on a user with cerebral palsy who successfully gained BCI control and played the classical Tic-Tac-Toe game against his caregiver.