After successfully finishing the course students can:
- Explain the origin and properties of the brain and EEG signals.
- Explain and apply methods for analysing and classifying ERPs in EEG signals.
- Explain different types of BCI paradigms and how to apply them in a BCI.
- Conduct neurophysiological data analysis using tools.
- Design and execute a small BCI experiment.
The course gives an introduction to Brain Computer Interfacing (BCI). The course will be geared towards knowledge and give an introduction into several BCI paradigms -- such as SSVEP, P300, N400, Imaginary movement -- signal acquisition, pre-processing techniques, classification methods and user feedback. Moreover, attention will be paid to the integration of standard Human Computer Interaction methods into the BCI domain.|
Students will be graded on basis of their final scientific report.
• Knowledge of real time systems, for example the course Real Time Systems (192130200)
• Basic Knowledge of (Digital) Signal Processing