A performance model of selection techniques for p300-based brain-computer interfaces

In this paper, we propose a model to predict the performance of selection techniques using Brain-Computer Interfaces based on P300 signals. This model is based on Markov theory and can compute both the time required to select a target and the number of visual flashes needed. We illustrate how to use this model with three different interaction techniques to select a target. A first experimental evaluation with three healthy participants shows a good match between the model and the experimental data. Author Keywords Brain-Computer Interface, Interaction Technique, P300 Evoked Potential, Markov Chains ACM Classification Keywords H5.2 [Information interfaces and presentation]: User Interfaces. - Theory and methods

• Type: Conference
• Year: 2009
• Where: CHI
• Authors: Jean-Baptiste Sauvan, Anatole Lécuyer, Fabien Lotte, Géry Casiez
• Keywords: Brain-computer Interface, CHI 2009, Human Computer Interaction, Interaction Technique, Model