An improved P300 pattern in BCI to catch user's attention
Related Experiment Video
Updated: Mar 7, 2026
P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
Published on: September 8, 2023
Jing Jin1, Hanhan Zhang1, Ian Daly2
1Key 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.
Objective:
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.
Approach:
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.
Main Results:
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.
Significance:
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.
