Learn More
OBJECTIVE This study investigates the feasibility of using a method based on electroencephalography (EEG) for deriving a driver's mental workload index. BACKGROUND The psychophysiological signals provide sensitive information for human functional states assessment in both laboratory and real-world settings and for building a new communication channel(More)
Event detection is the conversion of raw eye-tracking data into events--such as fixations, saccades, glissades, blinks, and so forth--that are relevant for researchers. In eye-tracking studies, event detection algorithms can have a serious impact on higher level analyses, although most studies do not accurately report their settings. We developed a(More)
A Brain-Computer Interface offers a new communication channel solely based on brain activity. The strong developments in the last decade led to an enormous improvement of the robustness and efficiency of the information flow in such systems. Nowadays, BCIs are used in medical care to establish a communication between the patient and his/her environment in(More)
Methods of statistical machine learning have recently proven to be very useful in contemporary brain-computer interface (BCI) research based on the discrimination of electroencephalogram (EEG) patterns. Because of this, many research groups develop new algorithms for both feature extraction and classification. However, until now, no large-scale comparison(More)