Difference between revisions of "Recognition of the user's focusing on the stimulation matrix"

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|title=Recognition of the user's focusing on the stimulation matrix
 
|title=Recognition of the user's focusing on the stimulation matrix
 
|image=B_p300_speller.jpg
 
|image=B_p300_speller.jpg
|description=A [http://en.wikipedia.org/wiki/P300_(Neuroscience) P300]-based [[Brain-Computer_Interface|BCI]] stimulates the user continuously, and the detection of a P300 designates the choice of the user. When the user is not paying attention to the interface, false positives are likely. The objective of this work is to avoid this problem; the analysis of the electroencephalogram (EEG) over the visual cortex (and possibly an analysis of P300s or of other biosignals) should tell when the user is looking at the interface
+
|description=A xxx stimulates the user continuously, and the detection of a P300 designates the choice of the user. When the user is not paying attention to the interface, false positives are likely. The objective of this work is to avoid this problem; the analysis of the electroencephalogram (EEG) over the visual cortex (and possibly an analysis of P300s or of other biosignals) should tell when the user is looking at the interface
 
|tutor=MatteoMatteucci; BernardoDalSeno
 
|tutor=MatteoMatteucci; BernardoDalSeno
 
|start=2009/10/01
 
|start=2009/10/01

Revision as of 00:07, 14 October 2009

Title: Recognition of the user's focusing on the stimulation matrix
B p300 speller.jpg

Image:B_p300_speller.jpg

Description: A xxx stimulates the user continuously, and the detection of a P300 designates the choice of the user. When the user is not paying attention to the interface, false positives are likely. The objective of this work is to avoid this problem; the analysis of the electroencephalogram (EEG) over the visual cortex (and possibly an analysis of P300s or of other biosignals) should tell when the user is looking at the interface
Tutor: MatteoMatteucci (matteo.matteucci@polimi.it), BernardoDalSeno (bernardo.dalseno@polimi.it)
Start: 2009/10/01
Students: 1 - 2
CFU: 5 - 20
Research Area: BioSignal Analysis
Research Topic: Brain-Computer Interface
Level: Bs, Ms
Type: Course, Thesis
Status: Active
Tools and instruments
Matlab, BCI2000, C++
EEG system
Bibliography
E. Donchin, K.M. Spencer, R. Wijesinghe. The Mental Prosthesis: Assessing the Speed of a P300-Based Brain-Computer Interface [1]