DocumentCode :
2632722
Title :
Extracting Single Trial Visual Evoked Potentials Using Iterative Generalized Eigen Value Decomposition
Author :
Hajipour, Sepideh ; Shamsollahi, Mohammad B. ; Mamaghanian, Hossein ; Abootalebi, Vahid
Author_Institution :
Biomed. Signal & Image Process. Lab. (BiSIPL), Sharif Univ. of Technol., Tehran
fYear :
2008
fDate :
16-19 Dec. 2008
Firstpage :
233
Lastpage :
237
Abstract :
The activity generated in the brain in response to external stimulations which is named the evoked potential (EP) is typically buried in the background EEG. Because of the low signal to noise ratio of EPs, it is difficult to record single trial evoked potentials. The traditional technique which is based on ensemble averaging destroys the dynamic information of single trials. In this paper, a new method has been proposed based on generalized eigen value decomposition to extract single trial EPs from single channel EEG recordings. The extraction of the N75-P100-N135 complex in simulated and actual visual evoked potentials is mainly taken under consideration. To illustrate the effectiveness of the proposed algorithm, it is compared with the iterative ICA method.
Keywords :
eigenvalues and eigenfunctions; electroencephalography; independent component analysis; iterative methods; medical signal processing; visual evoked potentials; N75-P100-N135 complex; brain; external stimulations; iterative ICA method; iterative generalized eigen value decomposition; signal to noise ratio; single channel EEG recordings; single trial evoked potentials; visual evoked potentials; Brain modeling; Data mining; Delay; Electroencephalography; Independent component analysis; Iterative algorithms; Iterative methods; Noise reduction; Testing; Wiener filter; Generalized eigen value decomposition; Single trial evoked potential; Visual evoked potential;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Information Technology, 2008. ISSPIT 2008. IEEE International Symposium on
Conference_Location :
Sarajevo
Print_ISBN :
978-1-4244-3554-8
Electronic_ISBN :
978-1-4244-3555-5
Type :
conf
DOI :
10.1109/ISSPIT.2008.4775708
Filename :
4775708
Link To Document :
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