DocumentCode :
3145808
Title :
A time-varying Gaussian model for the complex-valued EEG spectrum during mental imagery tasks
Author :
Aghaei, Amirhossein S. ; Plataniotis, Konstantinos N. ; Pasupathy, Subbarayan
Author_Institution :
Edward S. Rogers Sr. Dept. of Electr. & Comput. Eng., Univ. of Toronto, Toronto, ON, Canada
fYear :
2012
fDate :
25-30 March 2012
Firstpage :
669
Lastpage :
672
Abstract :
Recent findings in neuroscience have shown that the spectral components of electroencephalogram (EEG) signals convey information regarding the mental task not only in their power but also in their phase. This calls for the utilization of complex-valued spectrum, instead of the commonly used power spectral density, in designing the brain computer interfaces. This paper studies the complex-valued spectrum of the EEG signal recorded during mental imagery tasks, and provides a statistical model for the EEG spectral components. Motivated by the results of a recent work by the authors, this paper proposes a time-varying noncircularly-symmetric Gaussian model for complex-valued EEG spectrum during a mental imagery trial. It will be shown that the mean of this Gaussian model is constant over time, whereas its variance and pseudo-variance follow an autoregressive conditional heteroscedastic (ARCH) model. The validity of this model is then verified using statistical tests.
Keywords :
brain-computer interfaces; electroencephalography; medical signal processing; regression analysis; ARCH model; EEG spectral component; autoregressive conditional heteroscedastic model; brain computer interface; complex valued EEG spectrum; electroencephalogram signals; mental imagery tasks; neuroscience; pseudo variance; time varying Gaussian model; Adaptation models; Analytical models; Brain modeling; Computational modeling; Electroencephalography; Gaussian distribution; Market research; Brain computer interface; autoregressive conditional heteroscedasticity; complex-valued spectrum; improper complex Gaussian;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
Conference_Location :
Kyoto
ISSN :
1520-6149
Print_ISBN :
978-1-4673-0045-2
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2012.6287972
Filename :
6287972
Link To Document :
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