Name
Abstract | ||
|---|---|---|
An asynchronous hybrid brain-computer interface (BCI) system combining the P300 and steady-state visually evoked potentials (SSVEP) paradigms is introduced. A P300 base system is used for information transfer, and is augmented to include SSVEP for control state detection. The proposed system has been validated through off-line and online experiments. It is shown to achieve fast and accurate control state detection without significantly compromising the performance. For the two subjects who participated in the online experiments, the system achieved an average data transfer rate of 20.13 bits/min, with control state classification accuracy of more than 97%. |
Year | Venue | Keywords |
|---|---|---|
2010 | Aalborg | brain-computer interfaces,visual evoked potentials,p300 base system,ssvep,asynchronous hybrid brain-computer interface,control state classification accuracy,control state detection,information transfer,steady-state visually evoked potentials,accuracy,steady state,electroencephalography,brain computer interfaces,electric potential,visualization |
Field | DocType | ISSN |
Data rate units,Asynchronous communication,Information transfer,Visualization,Computer science,Brain–computer interface,Speech recognition,Steady state,Electroencephalography | Conference | 2219-5491 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rajesh Chandrasekhara Panicker | 1 | 38 | 3.76 |
| Sadasivan Puthusserypady | 2 | 181 | 27.49 |
| Ananda P. Pryana | 3 | 0 | 0.34 |
| Ying Sun | 4 | 224 | 19.86 |