title: An asynchronous P300 BCI with SSVEP-based control state detection.
abstract: In this paper, an asynchronous brain-computer interface (BCI) system combining the P300 and steady-state visually evoked potentials (SSVEPs) paradigms is proposed. The information transfer is accomplished using P300 event-related potential paradigm and the control state (CS) detection is achieved using SSVEP, overlaid on the P300 base system. Offline and online experiments have been performed with ten subjects to validate the proposed system. It is shown to achieve fast and accurate CS detection without significantly compromising the performance. In online experiments, the system is found to be capable of achieving an average data transfer rate of 19.05 bits/min, with CS detection accuracy of about 88%.
authors.affiliation: Department of Electrical and Computer Engineering, National University of Singapore, Singapore. rajesh.c@nus.edu.sg
authors.forename: Rajesh C
authors.initials: RC
authors.lastname: Panicker
authors.forename: Sadasivan
authors.initials: S
authors.lastname: Puthusserypady
authors.forename: Ying
authors.initials: Y
authors.lastname: Sun
mesh_terms: D000328:Adult; D000465:Algorithms; D019540:Area Under Curve; D004569:Electroencephalography / Q000379:methods*; D018913:Event-Related Potentials, P300 / Q000502:physiology*; D005074:Evoked Potentials, Visual / Q000502:physiology; D005260:Female; D006801:Humans; D008297:Male; D058117:Neural Prostheses; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*