@article{TobiasVoelkerGuneschetal.2012,
  author    = {Tobias, Kaufmann and V{\"o}lker, Stefan and Gunesch, Laura and K{\"u}bler, Andrea},
  title     = {Spelling is just a click away - a user-centered brain-computer interface including auto-calibration and predictive text entry},
  doi       = {10.3389/fnins.2012.00072},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-75739},
  year      = {2012},
  abstract  = {Brain-computer interfaces (BCI) based on event-related potentials (ERP) allow for selection of characters from a visually presented character-matrix and thus provide a communica- tion channel for users with neurodegenerative disease. Although they have been topic of research for more than 20 years and were multiply proven to be a reliable communication method, BCIs are almost exclusively used in experimental settings, handled by qualified experts. This study investigates if ERP-BCIs can be handled independently by laymen without expert support, which is inevitable for establishing BCIs in end-user's daily life situations. Furthermore we compared the classic character-by-character text entry against a predictive text entry (PTE) that directly incorporates predictive text into the character- matrix. N = 19 BCI novices handled a user-centered ERP-BCI application on their own without expert support. The software individually adjusted classifier weights and control parameters in the background, invisible to the user (auto-calibration). All participants were able to operate the software on their own and to twice correctly spell a sentence with the auto-calibrated classifier (once with PTE, once without). Our PTE increased spelling speed and, importantly, did not reduce accuracy. In sum, this study demonstrates feasi- bility of auto-calibrating ERP-BCI use, independently by laymen and the strong benefit of integrating predictive text directly into the character-matrix.},
  subject      = {Psychologie},
  language  = {en}
}
@article{MuenssingerHalderKleihetal.2010,
  author    = {M{\"u}nßinger, Jana I. and Halder, Sebastian and Kleih, Sonja C. and Furdea, Adrian and Raco, Valerio and H{\"o}sle, Adi and K{\"u}bler, Andrea},
  title     = {Brain Painting: first evaluation of a new brain-computer interface application with ALS-patients and healthy volunteers},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-68168},
  year      = {2010},
  abstract  = {Brain-computer interfaces (BCIs) enable paralyzed patients to communicate; however, up to date, no creative expression was possible. The current study investigated the accuracy and user-friendliness of P300-Brain Painting, a new BCI application developed to paint pictures using brain activity only. Two different versions of the P300-Brain Painting application were tested: A colored matrix tested by a group of ALS-patients (n = 3) and healthy participants (n = 10), and a black and white matrix tested by healthy participants (n = 10). The three ALS-patients achieved high accuracies; two of them reaching above 89\% accuracy. In healthy subjects, a comparison between the P300-Brain Painting application (colored matrix) and the P300-Spelling application revealed significantly lower accuracy and P300 amplitudes for the P300-Brain Painting application. This drop in accuracy and P300 amplitudes was not found when comparing the P300-Spelling application to an adapted, black and white matrix of the P300-Brain Painting application. By employing a black and white matrix, the accuracy of the P300-Brain Painting application was significantly enhanced and reached the accuracy of the P300-Spelling application. ALS-patients greatly enjoyed P300-Brain Painting and were able to use the application with the same accuracy as healthy subjects. P300-Brain Painting enables paralyzed patients to express themselves creatively and to participate in the prolific society through exhibitions.},
  subject      = {Psychologie},
  language  = {en}
}
@article{HalderHammerKleihetal.2013,
  author    = {Halder, Sebastian and Hammer, Eva Maria and Kleih, Sonja Claudia and Bogdan, Martin and Rosenstiel, Wolfgang and Birbaumer, Nils and K{\"u}bler, Andrea},
  title     = {Prediction of Auditory and Visual P300 Brain-Computer Interface Aptitude},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-77992},
  year      = {2013},
  abstract  = {Objective: Brain-computer interfaces (BCIs) provide a non-muscular communication channel for patients with late-stage motoneuron disease (e.g., amyotrophic lateral sclerosis (ALS)) or otherwise motor impaired people and are also used for motor rehabilitation in chronic stroke. Differences in the ability to use a BCI vary from person to person and from session to session. A reliable predictor of aptitude would allow for the selection of suitable BCI paradigms. For this reason, we investigated whether P300 BCI aptitude could be predicted from a short experiment with a standard auditory oddball. Methods: Forty healthy participants performed an electroencephalography (EEG) based visual and auditory P300-BCI spelling task in a single session. In addition, prior to each session an auditory oddball was presented. Features extracted from the auditory oddball were analyzed with respect to predictive power for BCI aptitude. Results: Correlation between auditory oddball response and P300 BCI accuracy revealed a strong relationship between accuracy and N2 amplitude and the amplitude of a late ERP component between 400 and 600 ms. Interestingly, the P3 amplitude of the auditory oddball response was not correlated with accuracy. Conclusions: Event-related potentials recorded during a standard auditory oddball session moderately predict aptitude in an audiory and highly in a visual P300 BCI. The predictor will allow for faster paradigm selection. Significance: Our method will reduce strain on patients because unsuccessful training may be avoided, provided the results can be generalized to the patient population.},
  subject      = {Psychologie},
  language  = {en}
}