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- Institut für Psychologie (23) (remove)
Tactile stimulation is less frequently used than visual for brain-computer interface (BCI) control, partly because of limitations in speed and accuracy. Non-visual BCI paradigms, however, may be required for patients who struggle with vision dependent BCIs because of a loss of gaze control. With the present study, we attempted to replicate earlier results by Herweg et al. (2016), with several minor adjustments and a focus on training effects and usability. We invited 16 healthy participants and trained them with a 4-class tactile P300-based BCI in five sessions. Their main task was to navigate a virtual wheelchair through a 3D apartment using the BCI. We found significant training effects on information transfer rate (ITR), which increased from a mean of 3.10–9.50 bits/min. Further, both online and offline accuracies significantly increased with training from 65% to 86% and 70% to 95%, respectively. We found only a descriptive increase of P300 amplitudes at Fz and Cz with training. Furthermore, we report subjective data from questionnaires, which indicated a relatively high workload and moderate to high satisfaction. Although our participants have not achieved the same high performance as in the Herweg et al. (2016) study, we provide evidence for training effects on performance with a tactile BCI and confirm the feasibility of the paradigm.
Data analytics as a field is currently at a crucial point in its development, as a commoditization takes place in the context of increasing amounts of data, more user diversity, and automated analysis solutions, the latter potentially eliminating the need for expert analysts. A central hypothesis of the present paper is that data visualizations should be adapted to both the user and the context. This idea was initially addressed in Study 1, which demonstrated substantial interindividual variability among a group of experts when freely choosing an option to visualize data sets. To lay the theoretical groundwork for a systematic, taxonomic approach, a user model combining user traits, states, strategies, and actions was proposed and further evaluated empirically in Studies 2 and 3. The results implied that for adapting to user traits, statistical expertise is a relevant dimension that should be considered. Additionally, for adapting to user states different user intentions such as monitoring and analysis should be accounted for. These results were used to develop a taxonomy which adapts visualization recommendations to these (and other) factors. A preliminary attempt to validate the taxonomy in Study 4 tested its visualization recommendations with a group of experts. While the corresponding results were somewhat ambiguous overall, some aspects nevertheless supported the claim that a user-adaptive data visualization approach based on the principles outlined in the taxonomy can indeed be useful. While the present approach to user adaptivity is still in its infancy and should be extended (e.g., by testing more participants), the general approach appears to be very promising.
Objectives
Virtual reality exposure therapy (VRET) is a promising treatment for patients with fear of driving. The present pilot study is the first one focusing on behavioral effects of VRET on patients with fear of driving as measured by a post-treatment driving test in real traffic.
Methods
The therapy followed a standardized manual including psychotherapeutic and medical examination, two preparative psychotherapy sessions, five virtual reality exposure sessions, a final behavioral avoidance test (BAT) in real traffic, a closing session, and two follow-up phone assessments after six and twelve weeks. VRE was conducted in a driving simulator with a fully equipped mockup. The exposure scenarios were individually tailored to the patients’ anxiety hierarchy. A total of 14 patients were treated. Parameters on the verbal, behavioral and physiological level were assessed.
Results
The treatment was helpful to overcome driving fear and avoidance. In the final BAT, all patients mastered driving tasks they had avoided before, 71% showed an adequate driving behavior as assessed by the driving instructor, and 93% could maintain their treatment success until the second follow-up phone call. Further analyses suggest that treatment reduces avoidance behavior as well as symptoms of posttraumatic stress disorder as measured by standardized questionnaires (Avoidance and Fusion Questionnaire: p < .10, PTSD Symptom Scale–Self Report: p < .05).
Conclusions
VRET in driving simulation is very promising to treat driving fear. Further research with randomized controlled trials is needed to verify efficacy. Moreover, simulators with lower configuration stages should be tested for a broad availability in psychotherapy.