title: A Hybrid Brain-Computer Interface Based on the Fusion of P300 and SSVEP Scores.
abstract: The present study proposes a hybrid brain-computer interface (BCI) with 64 selectable items based on the fusion of P300 and steady-state visually evoked potential (SSVEP) brain signals. With this approach, row/column (RC) P300 and two-step SSVEP paradigms were integrated to create two hybrid paradigms, which we denote as the double RC (DRC) and 4-D spellers. In each hybrid paradigm, the target is simultaneously detected based on both P300 and SSVEP potentials as measured by the electroencephalogram. We further proposed a maximum-probability estimation (MPE) fusion approach to combine the P300 and SSVEP on a score level and compared this approach to other approaches based on linear discriminant analysis, a naïve Bayes classifier, and support vector machines. The experimental results obtained from thirteen participants indicated that the 4-D hybrid paradigm outperformed the DRC paradigm and that the MPE fusion achieved higher accuracy compared with the other approaches. Importantly, 12 of the 13 participants, using the 4-D paradigm achieved an accuracy of over 90% and the average accuracy was 95.18%. These promising results suggest that the proposed hybrid BCI system could be used in the design of a high-performance BCI-based keyboard.
authors.forename: Erwei
authors.initials: E
authors.lastname: Yin
authors.forename: Timothy
authors.initials: T
authors.lastname: Zeyl
authors.forename: Rami
authors.initials: R
authors.lastname: Saab
authors.forename: Tom
authors.initials: T
authors.lastname: Chau
authors.forename: Dewen
authors.initials: D
authors.lastname: Hu
authors.forename: Zongtan
authors.initials: Z
authors.lastname: Zhou
mesh_terms: D000293:Adolescent; D000328:Adult; D001499:Bayes Theorem; D062207:Brain-Computer Interfaces; D016002:Discriminant Analysis; D004569:Electroencephalography; D004867:Equipment Design; D018913:Event-Related Potentials, P300 / Q000502:physiology*; D005073:Evoked Potentials, Somatosensory / Q000502:physiology*; D005074:Evoked Potentials, Visual / Q000502:physiology*; D005260:Female; D006801:Humans; D059032:Learning Curve; D008297:Male; D011597:Psychomotor Performance; D060388:Support Vector Machine; D055815:Young Adult