Dataset IIIb: Non-stationary 2-class BCI data
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چکیده
Short description: cued motor imagery with online feedback (non-stationary classifier) with 2 classes, and 3-4 sessions from 3 subjects. Aim: Non-stationary (i.e. time-varying) BCI data should be classified. It can be expected that time-varying classifier performs better than a stationary (static) classifier. Moreover, the response time of each method will be evaluated. EEG-data from three different subjects during a BCI experiment. The experiment consists of 3 sessions for each subject. Each session consists of 4 to 9 runs. The data of all runs was concatenated and converted into the GDF format [1]. The recordings were made with a bipolar EEG amplifier from g.tec. The EEG was sampled with 125 Hz, it was filtered between 0.5 and 30Hz with Notchfilter on.
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