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Study of Phase Relationships in ECoG Signals Using Hilbert-Huang Transforms

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 7366)

Abstract

This study investigates phase relationships between electrocorticogram (ECoG) signals through Hilbert-Huang Transform (HHT), combined with Empirical Mode Decomposition (EMD). We perform spatial and temporal filtering of the raw signals, followed by tuning the EMD parameters. It can be seen that carefully tuning of EMD filter, it is possible to capture distinct features of non-stationary data. This makes EMD, combined with HHT a valuable tool of complex brain signal analysis and modeling.

Keywords

  • Electrocorticogram (ECoG)
  • Hilbert Huang Transform (HHT)
  • Empirical Mode Decomposition (EMD)
  • Phase cone

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© 2012 Springer-Verlag Berlin Heidelberg

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Hossain, G., Myers, M.H., Kozma, R. (2012). Study of Phase Relationships in ECoG Signals Using Hilbert-Huang Transforms. In: Zhang, H., Hussain, A., Liu, D., Wang, Z. (eds) Advances in Brain Inspired Cognitive Systems. BICS 2012. Lecture Notes in Computer Science(), vol 7366. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31561-9_19

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  • DOI: https://doi.org/10.1007/978-3-642-31561-9_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31560-2

  • Online ISBN: 978-3-642-31561-9

  • eBook Packages: Computer ScienceComputer Science (R0)