DocumentCode :
1851021
Title :
Extraction of Steady State Visually Evoked Potential Signal and Estimation of Distribution Map from EEG Data
Author :
Washizawa, Y. ; Yamashita, Y. ; Tanaka, T. ; Cichocki, A.
Author_Institution :
RIKEN, Tokyo
fYear :
2007
fDate :
22-26 Aug. 2007
Firstpage :
5449
Lastpage :
5452
Abstract :
We propose a signal extraction method from multi-channel EEG signals and apply to extract steady state visually evoked potential (SSVEP) signal. SSVEP is a response to visual stimuli presented in the form of flushing patterns. By using several flushing patterns with different frequency, brain machine (computer) interface (BMI/BCI) can be realized. Therefore it is important to extract SSVEP signals from multi-channel EEG signals. At first, we estimate the power of the objective signal in each electrode. Estimation of the power is helpful in not only extraction of the signal but also drawing a distribution map of the signal, finding electrodes which have large SNR, and ranking electrodes in sort of information with respect to the power of the signal. Experimental results show that the proposed method 1) estimates more accurate power than existing methods, 2) estimates the global signal which has larger SNR than existing methods, and 3) allows us to draw a distribution map of the signal, and it conforms the biological theory.
Keywords :
biomedical electrodes; electroencephalography; feature extraction; medical signal processing; user interfaces; visual evoked potentials; brain machine interface; distribution map estimation; electrodes; flushing patterns; multichannel EEG signals; signal extraction; steady state visually evoked potential; visual stimuli; Brain computer interfaces; Computer interfaces; Data mining; Electrodes; Electroencephalography; Frequency; Independent component analysis; Signal to noise ratio; State estimation; Steady-state; Algorithms; Brain Mapping; Computer Simulation; Diagnosis, Computer-Assisted; Electroencephalography; Evoked Potentials, Visual; Humans; Models, Neurological; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Visual Cortex;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
Conference_Location :
Lyon
ISSN :
1557-170X
Print_ISBN :
978-1-4244-0787-3
Type :
conf
DOI :
10.1109/IEMBS.2007.4353578
Filename :
4353578
Link To Document :
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