Multichannel spectral pattern separation - An EEG processing application -

Authors:
Tomasz M. Rutkowski;Andrzej Cichocki; Toshihisa Tanaka;Danilo P. Mandic; Jianting Cao;Anca L. Ralescu
Affiliations:
Brain Science Institute RIKEN, Saitama, Japan;Brain Science Institute RIKEN, Saitama, Japan;Tokyo University of Agriculture and Technology, Japan;Imperial College London, UK;Saitama Institute of Technology, Japan;University of Cincinnati, OH, USA
Venue:
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Year:
2009

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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.