title: Two-dimensional auditory p300 speller with predictive text system.
abstract: P300-based Brain Computer Interfaces offer communication pathways which are independent of muscle activity. Mostly visual stimuli, e.g. blinking of different letters are used as a paradigm of interaction. Neural degenerative diseases like amyotrophic lateral sclerosis (ALS) also cause a decrease in sight, but the ability of hearing is usually unaffected. Therefore, the use of the auditory modality might be preferable. This work presents a multiclass BCI paradigm using two-dimensional auditory stimuli: cues are varying in pitch (high/medium/low) and location (left/middle/right). The resulting nine different classes are embedded in a predictive text system, enabling to spell a letter with a 9-class decision. Moreover, an unbalanced subtrial selection is investigated and compared to the well-established sequence-wise paradigm. Twelve healthy subjects participated in an online study to investigate these approaches.
authors.affiliation: Machine Learning Department, Berlin Institute of Technology, Germany. johannes.hoehne@tu-berlin.de
authors.forename: Johannes
authors.initials: J
authors.lastname: Hohne
authors.forename: Martijn
authors.initials: M
authors.lastname: Schreuder
authors.forename: Benjamin
authors.initials: B
authors.lastname: Blankertz
authors.forename: Michael
authors.initials: M
authors.lastname: Tangermann
mesh_terms: D000161:Acoustic Stimulation; D000328:Adult; D000465:Algorithms; D005260:Female; D006801:Humans; D008297:Male; D014584:User-Computer Interface