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Acoustics, Speech, and Signal Processing, IEEE International Conference on (2009)
Taipei, Taiwan
Apr. 19, 2009 to Apr. 24, 2009
ISBN: 978-1-4244-2353-8
pp: 373-376
Jianting Cao , Saitama Institute of Technology, Japan
Anca L. Ralescu , University of Cincinnati, OH, USA
Danilo P. Mandic , Imperial College London, UK
Tomasz M. Rutkowski , Brain Science Institute RIKEN, Saitama, Japan
Andrzej Cichocki , Brain Science Institute RIKEN, Saitama, Japan
Toshihisa Tanaka , Tokyo University of Agriculture and Technology, Japan
ABSTRACT
A problem of information separation in multichannel recordings is important in engineering applications such as brain computer/machine interfaces (BCI/BMI). Whereas this problem is not entirely new, engineering approaches connecting the mental states of humans and the observed electroencephalography (EEG) recordings are still in their infancy, mostly due to problems with electrophysiological denoising. The electrophysiological signals captured in form of the EEG carry brain activity in form of the neurophysiological components which are usually embedded in much higher power electrical muscle activity components (electromyography - EMG; electrooculography - EOG; etc.). In this paper we present an approach to remove muscular interference caused by eye-movements from EEG recorded during auditory experiments in an eight channel recording setting. This is achieved by analyzing the correlation of the oscillatory modes within a multichannel signal in the Hilbert domain. Simulations in a real world auditory BCI setting support the analysis.
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CITATION
Jianting Cao, Anca L. Ralescu, Danilo P. Mandic, Tomasz M. Rutkowski, Andrzej Cichocki, Toshihisa Tanaka, "Multichannel spectral pattern separation - An EEG processing application -", Acoustics, Speech, and Signal Processing, IEEE International Conference on, vol. 00, no. , pp. 373-376, 2009, doi:10.1109/ICASSP.2009.4959598
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