Brain Computer Interaction or Brain-Computer-interfaces (BCI) have been a topic of intense research in neuroscience/neuroengineering for the last decades. Controlling a machine just via thoughts is mainly used in clinical applications to enable e.g. paralyzed people interaction and communication with the outer world. However, more and more consumer products found their way on the market recently, to provide applications not only for handicapped people. Current solutions make it possible to control robot arms, entire exoskeletons, wheelchairs or even cars to regain mobility. They are used for stroke rehabilitation, as communication tools (so called brain-typers) or to measure stress and focus in everyday life. No matter how far we have come, these solutions still lack the necessary usability due to intense training sessions and their accuracy/reliability. Machine learning techniques might solve these problems in the future.
This seminar covers aspects of current challenges in Brain Computer Interaction and focuses on non-invasive EEG-based BCI techniques. Attendees will investigate a particular challenge in this field in groups of four based on scientific publications. We will provide a first collection of papers related to the chosen research topic. At the end of the seminar, you are supposed to provide a current state-of-the art concerning your topic as well as ideas for further research, to overcome existing problems in this field.
Each group will undergo the following assessments:
- 20 min presentation of one of the provided papers (per person)
- Further literature research concerning the topic
- 20 min group presentation of current state-of-the art
- Short paper (6 pages)
date and time
Wednesdays, 2pm-4pm at DFKI (room Reuse)
Summer term 2018