Information preserving empirical mode decomposition for filtering field potentials

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    Abstract

    This paper presents a concept of using the empirical mode decomposition (EMD) as a filtering tool to extract information-preserving intrinsic mode functions (IMFs) in an adaptive manner. The approach is tested on several local field potentials (LFPs) and information quantification is carried out in spectral domain using Shannon's Information. The study suggests that not all IMFs are information carriers. It is found that the 1st IMF carries 60-80% of the total information from original LFP and few informative IMFs are usually the main information carriers. Adding more IMFs does not increase the information level. For different datasets, the order of the informative IMFs varies and by using information preserving EMD, only few IMFs are retained to provide a simplified representation of underlying oscillations contained in LFPs. © 2009 Springer Berlin Heidelberg.
    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.
    Pages226-233
    Number of pages7
    Volume5788
    DOIs
    Publication statusPublished - 2009
    Event10th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2009 - Burgos
    Duration: 1 Jul 2009 → …

    Conference

    Conference10th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2009
    CityBurgos
    Period1/07/09 → …

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