Brain-Computer Interface research has developed to a very broad field. It covers the understanding of brain processes, experimental design, recording of brain activity, signal processing and feature extraction. With machine learning methods brain signals can be decoded and translated to control signals for a large variety of applications. Artifact handling is as important as setting potential end users into the center of the resarch.
The main research lines are:
movement decoding | error processing | EEG-based neuroprosthesis control | communication with BCI in patients with disorders of consciousness | hybrid BCI systems | the human somatosensory system | functional brain mapping | BCIs in assistive technology | biosignal analysis and machine learning | Neuro Information Systems research | BCIs for autonomous mobility