TY - GEN
T1 - A performance model of selection techniques for P300-based brain-computer interfaces
AU - Sauvan, Jean Baptiste
AU - Lécuyer, Anatole
AU - Lotte, Fabien
AU - Casiez, Géry
PY - 2009/1/1
Y1 - 2009/1/1
N2 - 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.
AB - 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.
KW - Brain-computer interface
KW - Interaction technique
KW - Markov chains
KW - P300 evoked potential
U2 - 10.1145/1518701.1519037
DO - 10.1145/1518701.1519037
M3 - Conference contribution
AN - SCOPUS:84892468908
SN - 9781605582474
T3 - Conference on Human Factors in Computing Systems - Proceedings
SP - 2205
EP - 2208
BT - CHI 2009
PB - Association for Computing Machinery
T2 - 27th International Conference Extended Abstracts on Human Factors in Computing Systems, CHI EA 2009
Y2 - 4 April 2009 through 9 April 2009
ER -