@phdthesis{Herweg2016,
  author    = {Herweg, Andreas},
  title     = {Beyond the state of the art, towards intuitive and reliable non-visual Brain-Computer-Interfacing},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-133447},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2016},
  abstract  = {For the present work three main goals were formulated: goal 1 To design a tactile BCI used for mobility which is intuitive (G1.1), reliable and fast while being usable by participants aged 50 years and above. goal 2 To design an auditory BCI used for communication which is intuitive and reliable. goal 3 To examine the effects of training on tactile and auditory BCI performance. Three studies were performed to achieve these goals. In the first study nine participants aged above 50 years performed a five-session training after which eight participants were able to navigate a virtual wheelchair with mean accuracy above 95\% and an ITR above 20 bits / min. In the second study 15 participants, four of them endusers with motor-impairment, were able to communicate meaningful with high accuracies using an auditory BCI. In the third study nine healthy and nine visually impaired participants (regarded as sensory experts for non-visual perception) performed tactile, auditory and visual (for healthy participants only) copy tasks. Participants with trained perception significantly outperformed control participants for tactile but not for auditory performance. Tactile performance of sensory experts was on equal levels as the visual performance of control participants. We were able to demonstrate viability of intuitive gazeindependent tactile and auditory BCI. Our tactile BCI performed on levels similar to those of visual BCI, outperforming current tactile BCI protocols. Furthermore, we were able to demonstrate significant beneficial effect of training on tactile BCI performance. Our results demonstrate previously untapped potential for tactile BCI and avenues for future research in the field of gaze-independent BCI.},
  subject      = {Gehirn-Computer-Schnittstelle},
  language  = {en}
}