Name
Abstract | ||
|---|---|---|
Brain computer interface (BCI) speller is an important issue in BCI research. In this paper, we propose a novel spelling paradigm for enhancing the performance of BCI speller. In our approach, the target character is detected by the combination of the P300 potential and the steady-state visual evoked potential (SSVEP). Specifically, the P300 detection mechanism and the SSVEP detection mechanism are employed as two sub-spellers for identifying the number of the subarea and location of target character, respectively and simultaneously. The experimental results show that the information transfer rate (ITR) of our BCI system was significantly improved compared to the traditional BCI approaches, i.e. P300 speller and SSVEP speller. © 2013 Springer-Verlag Berlin Heidelberg. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-42057-3-47 | IScIDE |
Keywords | Field | DocType |
brain computer interface (bci) speller,electroencephalogram (eeg),hybrid bci,p300,steady-state visual evoked potential (ssvep) | Information transfer,Computer science,Brain–computer interface,Speech recognition,Spelling | Conference |
Volume | Issue | ISSN |
8261 LNCS | null | 16113349 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Erwei Yin | 1 | 110 | 9.12 |
| Jun Jiang | 2 | 0 | 0.68 |
| Yang Yu | 3 | 38 | 5.71 |
| Jingsheng Tang | 4 | 9 | 3.33 |
| Zongtan Zhou | 5 | 412 | 33.89 |
| Dewen Hu | 6 | 1290 | 101.20 |