Title :
Target Selection With Hybrid Feature for BCI-Based 2-D Cursor Control
Author :
Long, Jinyi ; Li, Yuanqing ; Yu, Tianyou ; Gu, Zhenghui
Author_Institution :
Sch. of Autom. Sci. & Eng., South China Univ. of Technol., Guangzhou, China
Abstract :
To control a cursor on a monitor screen, a user generally needs to perform two tasks sequentially. The first task is to move the cursor to a target on the monitor screen (termed a 2-D cursor movement), and the second task is either to select a target of interest by clicking on it or to reject a target that is not of interest by not clicking on it. In a previous study, we implemented the former function in an EEG-based brain-computer interface system using motor imagery and the P300 potential to control the horizontal and vertical cursor movements, respectively. In this study, the target selection or rejection functionality is implemented using a hybrid feature from motor imagery and the P300 potential. Specifically, to select the target of interest, the user must focus his or her attention on a flashing button to evoke the P300 potential, while simultaneously maintaining an idle state of motor imagery. Otherwise, the user performs left-/right-hand motor imagery without paying attention to any buttons to reject the target. Our data analysis and online experimental results validate the effectiveness of our approach. The proposed hybrid feature is shown to be more effective than the use of either the motor imagery feature or the P300 feature alone. Eleven subjects attended our online experiment, in which a trial involved sequential 2-D cursor movement and target selection. The average duration of each trial and average accuracy of target selection were 18.19 s and 93.99% , respectively, and each target selection or rejection event was performed within 2 s.
Keywords :
bioelectric potentials; brain-computer interfaces; electroencephalography; medical signal processing; BCI-based 2D cursor control; EEG-based brain-computer interface system; P300 potential; hybrid feature; left hand motor imagery; motor imagery feature; rejection functionality; right hand motor imagery; sequential 2D cursor movement; Accuracy; Ash; Data analysis; Electroencephalography; Feature extraction; Image color analysis; Support vector machines; Brain–computer interface (BCI); EEG; P300 potential; cursor; hybrid feature; motor imagery; Adult; Biofeedback, Psychology; Brain; Computer Peripherals; Electrocardiography; Evoked Potentials; Female; Humans; Imagination; Male; Motion Perception; User-Computer Interface;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2011.2167718