Brain-Computer Interface
This research topic belongs to the research area BioSignal Analysis.
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).
Click here for a brief description of the Research Area, taken from the AirLab website.
Contents
Ongoing Projects
Projects on this topic:
Project proposals
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Finished Projects
- Characterization of the NIA signal
- Stimulus tagging using aperiodic visual stimulation in a VEP-based BCI
- 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* 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
Equipment
How to
Publications
You can find other publications in the BCI field by AIRLab members involved in this topic (see above) on their home pages.
Journals
B. Dal Seno, L. Mainardi, and M. Matteucci. The Utility metric: A novel method to assess the overall performance of discrete brain-computer interfaces. IEEE Transactions on Neural Systems and Rehabilitation Engineering, pages 20-28, February 2010.
B. Dal Seno, M. Matteucci, and L. Mainardi. On-line detection of P300 and error potentials in a BCI speller. Computational Intelligence and Neuroscience, Special Issue on Processing of Brain Signals by Using Hemodynamic and Neuroelectromagnetic Modalities, Article ID 307254, 5 pages, 2010.
PhD Theses
B. Dal Seno. Toward An Integrated P300- And ErrP-Based Brain-Computer Interface. Ph.D. dissertation, Politecnico di Milano, 2009.
Media
- 22 Jan 2009: Repubblica TV report on Lurch and BCI (in Italian)
- Aug 2008: RAI TGLeonardo report on Airlab research (in Italian). The video is a fragment of a longer report on mind and intelligence.
