Asynchronous P300 BCI: SSVEP-based control state detection

Author

Panicker, Rajesh C. ; Puthusserypady, Sadasivan ; Pryana, Ananda P. ; Ying Sun

Author_Institution

Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore, Singapore

fYear

2010

fDate

23-27 Aug. 2010

Firstpage

934

Lastpage

938

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%.

Keywords

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; Brain modeling; Brain-computer interfaces; Electric potential; Electroencephalography; Steady-state; Visualization;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Conference, 2010 18th European

Conference_Location

Aalborg

ISSN

2219-5491

Type

conf

Filename

7096578