title: Towards SSVEP-based, portable, responsive Brain-Computer Interface.
abstract: A Brain-Computer Interface in motion control application requires high system responsiveness and accuracy. SSVEP interface consisted of 2-8 stimuli and 2 channel EEG amplifier was presented in this paper. The observed stimulus is recognized based on a canonical correlation calculated in 1 second window, ensuring high interface responsiveness. A threshold classifier with hysteresis (T-H) was proposed for recognition purposes. Obtained results suggest that T-H classifier enables to significantly increase classifier performance (resulting in accuracy of 76%, while maintaining average false positive detection rate of stimulus different then observed one between 2-13%, depending on stimulus frequency). It was shown that the parameters of T-H classifier, maximizing true positive rate, can be estimated by gradient-based search since the single maximum was observed. Moreover the preliminary results, performed on a test group (N=4), suggest that for T-H classifier exists a certain set of parameters for which the system accuracy is similar to accuracy obtained for user-trained classifier.
authors.forename: Piotr
authors.initials: P
authors.lastname: Kaczmarek
authors.forename: Pawel
authors.initials: P
authors.lastname: Salomon
mesh_terms: D000465:Algorithms; D001921:Brain; D062207:Brain-Computer Interfaces; D004569:Electroencephalography; D005074:Evoked Potentials, Visual; D010775:Photic Stimulation; D014584:User-Computer Interface