A passive Brain Computer Interface (BCI) is a system that responds to the spontaneously produced brain activity of its user and could be used to develop interactive task support. A human-machine system that could benefit from brain-based task support is the driver-car interaction system. To investigate the feasibility of such a system to detect changes in visuomotor workload, 34 drivers were exposed to several levels of driving demand in a driving simulator. Driving demand was manipulated by varying driving speed and by asking the drivers to comply to individually set lane keeping performance targets. Differences in the individual driver's workload levels were classified by applying the Common Spatial Pattern (CSP) and Fisher's linear discriminant analysis to frequency filtered electroencephalogram (EEG) data during an off line classification study. Several frequency ranges, EEG cap configurations, and condition pairs were explored. It was found that classifications were most accurate when based on high frequencies, larger electrode sets, and the frontal electrodes. Depending on these factors, classification accuracies across participants reached about 95% on average. The association between high accuracies and high frequencies suggests that part of the underlying information did not originate directly from neuronal activity. Nonetheless, average classification accuracies up to 75–80% were obtained from the lower EEG ranges that are likely to reflect neuronal activity. For a system designer, this implies that a passive BCI system may use several frequency ranges for workload classifications.

Background: Irritable bowel syndrome (IBS) can have a significant negative impact on quality of life, mood and wellbeing. The aim of this study was to investigate the association between experiencing IBS symptoms and insomnia, and perceived health status. Method: An online survey was conducted among n = 1950 Dutch university students (83.6% women). IBS was assessed with the Birmingham IBS Symptom Questionnaire, quality of life with the WHO-5 wellbeing index, and sleep outcomes with the SLEEP-50 questionnaire. Perceived immune functioning and general health were assessed using 1-item scales. Results: IBS symptom severity was significantly associated with insomnia complaints (r = 0.32, p = 0.0001), sleep quality (r = −0.21, p = 0.0001), sleep onset latency (r = 0.11, p = 0.0001) and the number of nightly awakenings (r = 0.24, p = 0.0001). Total sleep time was not significantly associated with IBS symptom severity. Significant correlations were also found between IBS symptom severity and perceived general health (r = −0.30, p = 0.0001), perceived immune functioning (r= −0.25, p = 0.0001), and quality of life (r = −0.24, p = 0.0001). Conclusions: Experiencing IBS complaints is associated with reduced perceived immune functioning, a poorer perception of general health, and sleep disturbances. These effects are reflected in a significantly lower reported quality of life in subjects with more IBS and/or sleep complaints.