Exploratory data analysis by genetic feature extraction

Title:	Exploratory data analysis by genetic feature extraction	Image:Evolve1at300dpi.gif
Description:	Understanding the waves in EEG signals is an hard task and psicologists often need automatic tools to perform this task. In this project we are interested in using a genetic algorithm developed for P300 feature extraction in order to extract useful informations from Error Potentials. The project is a collaboration with the psicology department od Padua University. B. Dal Seno, M. Matteucci, and L. Mainardi. "A genetic algorithm for automatic feature extraction in P300 detection" (http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf) B. Dal Seno, M. Matteucci, L. Mainardi, F. Piccione, and S. Silvoni. "Single-trial P300 detection in healthy and ALS subjects by means of a genetic algorithm" (http://home.dei.polimi.it/dalseno/papers/2008/grazGa08.pdf)
Tutor:	MatteoMatteucci (matteo.matteucci@polimi.it)
Start:	2009/10/01
Students:	1 - 2
CFU:	5 - 20
Research Area:	BioSignal Analysis
Research Topic:	Brain-Computer Interface
Level:	Ms
Type:	Course, Thesis
Status:	Closed