@phdthesis{Eidel2020,
  author    = {Eidel, Matthias T. A. M.},
  title     = {Training Effects of a Tactile Brain-Computer Interface System During Prolonged Use by Healthy And Motor-Impaired People},
  doi       = {10.25972/OPUS-20851},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-208511},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2020},
  abstract  = {Background - Brain-Computer Interfaces (BCI) enable their users to interact and communicate with the environment without requiring intact muscle control. To this end, brain activity is directly measured, digitized and interpreted by the computer. Thus, BCIs may be a valuable tool to assist severely or even completely paralysed patients. Many BCIs, however, rely on neurophysiological potentials evoked by visual stimulation, which can result in usability issues among patients with impaired vision or gaze control. Because of this, several non-visual BCI paradigms have been developed. Most notably, a recent study revealed promising results from a tactile BCI for wheelchair control. In this multi-session approach, healthy participants used the BCI to navigate a simulated wheelchair through a virtual apartment, which revealed not only that the BCI could be operated highly efficiently, but also that it could be trained over five sessions. The present thesis continues the research on this paradigm in order to - confirm its previously reported high performance levels and trainability - reveal the underlying factors responsible for observed performance increases - establish its feasibility among potential impaired end-users Methods - To approach these goals, three studies were conducted with both healthy participants and patients with amyotrophic lateral sclerosis (ALS). Brain activity during BCI operation was recorded via electroencephalography (EEG) and interpreted using a machine learning-based linear classifier. Wheelchair navigation was executed according to the classification results and visualized on a monitor. For offline statistical analysis, neurophysiological features were extracted from EEG data. Subjective data on usability were collected from all participants. Two specialized experiments were conducted to identify factors for training. Results and Discussion - Healthy participants: Results revealed positive effects of training on BCI performances and their underlying neurophysiological potentials. The paradigm was confirmed to be feasible and (for a non-visual BCI) highly efficient for most participants. However, some had to be excluded from analysis of the training effects because they could not achieve meaningful BCI control. Increased somatosensory sensitivity was identified as a possible mediator for training-related performance improvements. Participants with ALS: Out of seven patients with various stages of ALS, five could operate the BCI with accuracies significantly above chance level. Another ALS patient in a state of near-complete paralysis trained with the BCI for several months. Although no effects of training were observed, he was consistently able to operate the system above chance level. Subjective data regarding workload, satisfaction and other parameters were reported. Significance - The tactile BCI was evaluated on the example of wheelchair control. In the future, it could help impaired patients to regain some lost mobility and self-sufficiency. Further, it has the potential to be adapted to other purposes, including communication. Once visual BCIs and other assistive technologies fail for patients with (progressive) motor impairments, vision-independent paradigms such as the tactile BCI may be among the last remaining alternatives to interact with the environment. The present thesis has strongly confirmed the general feasibility of the tactile paradigm for healthy participants and provides first clues about the underlying factors of training. More importantly, the BCI was established among potential end-users with ALS, providing essential external validity.},
  subject      = {Myatrophische Lateralsklerose},
  language  = {en}
}