A hierarchical stimulus presentation paradigm for a P300‐based Hangul speller

We propose a hierarchical stimulus presentation paradigm for a P300‐based Hangul (Korean script) input system. A P300‐based input system (or speller) is one of the most promising noninvasive brain‐computer interface (BCI) applications based on its direct applicability in many computer programs. Although the previous row/column stimulus presentation paradigm has been well‐suited to the English input, it may not be optimal for a Hangul input because Hangul has a distinct hierarchical structure. To overcome the limitation of the previous paradigms, we developed a new P300‐based Hangul input system by taking the unique hierarchical structure of Hangul into account for creating a hierarchical stimulus presentation paradigm. By using the hierarchical structure, we can effectively reduce the window size of the interface without loss of classification accuracy. A performance comparison shows that the hierarchical paradigm exhibits higher classification accuracy than the row/column paradigm even with a smaller window size. Thus, the proposed hierarchical paradigm is more efficient to spell Hangul and will be more useful for BCI‐based Hangul input for a text messenger, e‐mail program, word processor and other similar applications. © 2011 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 21, 131–138, 2011

[1]  M Salvaris,et al.  Visual modifications on the P300 speller BCI paradigm , 2009, Journal of neural engineering.

[2]  Pavel Pudil,et al.  Introduction to Statistical Pattern Recognition , 2006 .

[3]  E. W. Sellers,et al.  Toward enhanced P300 speller performance , 2008, Journal of Neuroscience Methods.

[4]  U. Hoffmann,et al.  A Boosting Approach to P300 Detection with Application to Brain-Computer Interfaces , 2005, Conference Proceedings. 2nd International IEEE EMBS Conference on Neural Engineering, 2005..

[5]  J. Wolpaw,et al.  A novel P300-based brain–computer interface stimulus presentation paradigm: Moving beyond rows and columns , 2010, Clinical Neurophysiology.

[6]  Rajesh P. N. Rao,et al.  Control of a humanoid robot by a noninvasive brain–computer interface in humans , 2008, Journal of neural engineering.

[7]  G. Pfurtscheller,et al.  Brain-Computer Interfaces for Communication and Control. , 2011, Communications of the ACM.

[8]  E. Donchin,et al.  Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. , 1988, Electroencephalography and clinical neurophysiology.

[9]  Haihong Zhang,et al.  A Brain-Controlled Wheelchair Based on P300 and Path Guidance , 2006, The First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, 2006. BioRob 2006..

[10]  S M M Martens,et al.  Overlap and refractory effects in a brain–computer interface speller based on the visual P300 event-related potential , 2009, Journal of neural engineering.

[11]  C. Cinel,et al.  P300-Based BCI Mouse With Genetically-Optimized Analogue Control , 2008, IEEE Transactions on Neural Systems and Rehabilitation Engineering.