@article{HalderHammerKleihetal.2013,
  author    = {Halder, Sebastian and Hammer, Eva Maria and Kleih, Sonja Claudia and Bogdan, Martin and Rosenstiel, Wolfgang and Birbaumer, Niels and K{\"u}bler, Andrea},
  title     = {Prediction of Auditory and Visual P300 Brain-Computer Interface Aptitude},
  series = {PLoS ONE},
  volume    = {8},
  journal   = {PLoS ONE},
  number    = {2},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-130327},
  pages     = {e53513},
  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.},
  language  = {en}
}
@article{KueblerHolzRiccioetal.2014,
  author    = {K{\"u}bler, Andrea and Holz, Elisa M. and Riccio, Angela and Zickler, Claudia and Kaufmann, Tobias and Kleih, Sonja C. and Staiger-S{\"a}lzer, Pit and Desideri, Lorenzo and Hoogerwerf, Evert-Jan and Mattia, Donatella},
  title     = {The User-Centered Design as Novel Perspective for Evaluating the Usability of BCI-Controlled Applications},
  doi       = {10.1371/journal.pone.0112392},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-111051},
  year      = {2014},
  abstract  = {Albeit research on brain-computer interfaces (BCI) for controlling applications has expanded tremendously, we still face a translational gap when bringing BCI to end-users. To bridge this gap, we adapted the user-centered design (UCD) to BCI research and development which implies a shift from focusing on single aspects, such as accuracy and information transfer rate (ITR), to a more holistic user experience. The UCD implements an iterative process between end-users and developers based on a valid evaluation procedure. Within the UCD framework usability of a device can be defined with regard to its effectiveness, efficiency, and satisfaction. We operationalized these aspects to evaluate BCI-controlled applications. Effectiveness was regarded equivalent to accuracy of selections and efficiency to the amount of information transferred per time unit and the effort invested (workload). Satisfaction was assessed with questionnaires and visual-analogue scales. These metrics have been successfully applied to several BCI-controlled applications for communication and entertainment, which were evaluated by end-users with severe motor impairment. Results of four studies, involving a total of N = 19 end-users revealed: effectiveness was moderate to high; efficiency in terms of ITR was low to high and workload low to medium; depending on the match between user and technology, and type of application satisfaction was moderate to high. The here suggested evaluation metrics within the framework of the UCD proved to be an applicable and informative approach to evaluate BCI controlled applications, and end-users with severe impairment and in the locked-in state were able to participate in this process.},
  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}
}