A Brain-Computer Interface (BCI) is an experimental communication system that allows an individual to control a device by using signals from the brain (e.g., electroencephalography -- EEG).
You can find a longer description on the AIRLab page.
The BCI project is in the BioSignal_Analysis area.
- A genetic algorithm for automatic feature extraction from EEG data
- Graphical user interface for an autonomous wheelchair
- Online automatic tuning of the number of repetitions in a P300-based BCI
There are various proposal for students interested in projects/thesis in the field of brain-computer interfaces:
- Predictive BCI Speller based on Motor Imagery (Master thesis, Tiziano D'Albis)
- Feature Selection and Extraction for a BCI based on motor imagery (Master thesis, Francesco Amenta)
- Integrating Motor Imagery and Error Potentials in a Brain-Computer Interface (Master Thesis, Paolo Calloni)
- Ocular Artifacts Filter implementation for a BCI based on motor imagery (First Level thesis, Fabio Beltramini)
- Reproduction of an algorithm for the recognition of error potentials
- Online P300 and ErrP recognition with BCI2000 (Master thesis, Andrea Sgarlata).
- Tesi di Carlo Gimondi e Luisella Messana
- Tesi di Gianmaria Visconti
- Tesi di Francesco Cartella
You can find publications in the BCI field by Airlab members on their home pages: