• DocumentCode
    1457163
  • Title

    Higher-order spectral analysis of burst patterns in EEG

  • Author

    Muthuswamy, Jitendran ; Sherman, David Lee ; Thakor, Nitish V.

  • Author_Institution
    Dept. of Biomed. Eng., Johns Hopkins Univ., Baltimore, MD, USA
  • Volume
    46
  • Issue
    1
  • fYear
    1999
  • Firstpage
    92
  • Lastpage
    99
  • Abstract
    Burst suppression patterns in electroencephalograms (EEG´s) have been observed in a variety of situations including recovery of a subject from a traumatic brain injury. They are associated with grave prognostic outcomes in neonates. The authors study power spectral parameters and bispectral parameters of the EEG at baseline, during early recovery from an asphyxic arrest (EEG burst patterns) and during late recovery after EEG evolves into a more continuous activity. The bicoherence indexes, which indicate the degree of phase coupling between two frequency components of a signal, are significantly higher within the δ-θ band of the EEG bursts than in the baseline or late recovery waveforms. The bispectral parameters show a more detectable trend than the power spectral parameters. In the second part of the study, the authors looked into the possibility of higher (>2)-order nonlinearities in the EEG bursts using the diagonal slices of the polyspectrum. The diagonal elements of the polyspectrum reveal the presence of self-frequency and self-phase coupling of orders higher than two in majority of the EEG bursts studied. The bicoherence indexes and the diagonal elements of the polyspectrum strongly indicate the presence of nonlinearities of order two and in many cases higher, in the EEG generator during episodes of bursting. This indication of nonlinearity in EEG signals provides a novel quantitative measure of brain´s response to injury.
  • Keywords
    electroencephalography; medical signal processing; spectral analysis; /spl delta/-/spl theta/ band; EEG burst patterns; asphyxic arrest; bicoherence indexes; brain´s response to injury; electrodiagnostics; higher-order nonlinearities; higher-order spectral analysis; phase coupling; polyspectrum; signal frequency components; Biomedical engineering; Biomedical measurements; Brain injuries; Central nervous system; Electroencephalography; Epilepsy; Frequency; Pediatrics; Sleep; Spectral analysis; Animals; Asphyxia; Chi-Square Distribution; Electroencephalography; Hypoxia, Brain; Mathematics; Swine;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/10.736762
  • Filename
    736762