title: SSVEP-BCI implementation for 37-40 Hz frequency range.
abstract: This work presents a Brain-Computer Interface (BCI) based on Steady State Visual Evoked Potentials (SSVEP), using higher stimulus frequencies (>30 Hz). Using a statistical test and a decision tree, the real-time EEG registers of six volunteers are analyzed, with the classification result updated each second. The BCI developed does not need any kind of settings or adjustments, which makes it more general. Offline results are presented, which corresponds to a correct classification rate of up to 99% and a Information Transfer Rate (ITR) of up to 114.2 bits/min.
authors.affiliation: Department of Engineering and Computation, North Center, CEUNES, Federal University of Espírito Santo, São Mateus, Brazil. sandramuller@ceunes.ufes.br
authors.forename: Sandra Mara Torres
authors.initials: SM
authors.lastname: Müller
authors.forename: Pablo F
authors.initials: PF
authors.lastname: Diez
authors.forename: Teodiano Freire
authors.initials: TF
authors.lastname: Bastos-Filho
authors.forename: Mário
authors.initials: M
authors.lastname: Sarcinelli-Filho
authors.forename: Vicente
authors.initials: V
authors.lastname: Mut
authors.forename: Eric
authors.initials: E
authors.lastname: Laciar
mesh_terms: D000465:Algorithms; D001331:Automation; D001921:Brain / Q000473:pathology*; D003142:Communication; D003143:Communication Devices for People with Disabilities; D003663:Decision Trees; D004569:Electroencephalography / Q000379:methods; D004867:Equipment Design; D005074:Evoked Potentials, Visual; D006801:Humans; D008328:Man-Machine Systems; D015233:Models, Statistical; D012371:Robotics; D012815:Signal Processing, Computer-Assisted; D014584:User-Computer Interface