Abstract
Human brains expose the possibility to be connected directly to the intelligent computing applications in form of brain computer/ machine interfacing (BCI/BMI) technologies. Neurophysiological signals and especially electroencephalogram (EEG) are the forms of brain electrical activity which can be easily captured and utilized for BCI/BMI applications. Those signals are unfortunately highly contaminated by noise due to a very low level of electrophysiological signals and presence of different devices in the environment creating electromagnetic interference. In the proposed approach we first decompose each of the recorded channels, in multichannel EEG recording environment, into intrinsic mode functions (IMF) which are a result of empirical mode decomposition (EMD) extended to multichannel analysis in this paper. We present novel and interesting results on human mental and cognitive states estimation based on analysis of the above mentioned stimuli-related IMF components.
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Rutkowski, T.M., Mandic, D.P., Cichocki, A., Przybyszewski, A.W. (2008). EMD Approach to Multichannel EEG Data - The Amplitude and Phase Synchrony Analysis Technique. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues. ICIC 2008. Lecture Notes in Computer Science, vol 5226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87442-3_17
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DOI: https://doi.org/10.1007/978-3-540-87442-3_17
Publisher Name: Springer, Berlin, Heidelberg
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