title: An improved P300 pattern in BCI to catch user's attention.
abstract: Brain-computer interfaces (BCIs) can help patients who have lost control over most muscles but are still conscious and able to communicate or interact with the environment. One of the most popular types of BCI is the P300-based BCI. With this BCI, users are asked to count the number of appearances of target stimuli in an experiment. To date, the majority of visual P300-based BCI systems developed have used the same character or picture as the target for every stimulus presentation, which can bore users. Consequently, users attention may decrease or be negatively affected by adjacent stimuli.
  
  
  
  In this study, a new stimulus is presented to increase user concentration. Honeycomb-shaped figures with 1-3 red dots were used as stimuli. The number and the positions of the red dots in the honeycomb-shaped figure were randomly changed during BCI control. The user was asked to count the number of the dots presented in each flash instead of the number of times they flashed. To assess the performance of this new stimulus, another honeycomb-shaped stimulus, without red dots, was used as a control condition.
  
  
  
  The results showed that the honeycomb-shaped stimuli with red dots obtained significantly higher classification accuracies and information transfer rates (p  <  0.05) compared to the honeycomb-shaped stimulus without red dots.
  
  
  
  The results indicate that this proposed method can be a promising approach to improve the performance of the BCI system and can be an efficient method in daily application.
authors.affiliation: Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, People's Republic of China.
authors.forename: Jing
authors.initials: J
authors.lastname: Jin
authors.forename: Hanhan
authors.initials: H
authors.lastname: Zhang
authors.forename: Ian
authors.initials: I
authors.lastname: Daly
authors.forename: Xingyu
authors.initials: X
authors.lastname: Wang
authors.forename: Andrzej
authors.initials: A
authors.lastname: Cichocki
mesh_terms: D001288:Attention / Q000502:physiology*; D062207:Brain-Computer Interfaces; D004569:Electroencephalography / Q000379:methods*; D018913:Event-Related Potentials, P300 / Q000502:physiology*; D006801:Humans; D010775:Photic Stimulation / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013647:Task Performance and Analysis; D014796:Visual Perception / Q000502:physiology*