• DocumentCode
    3183451
  • Title

    Tracking non-stationary spectral peak structure in EEG data

  • Author

    Prerau, M.J. ; Purdon, P.L. ; Eden, Uri T.

  • Author_Institution
    Dept. of Anesthesia, Critical Care, & Pain Med., Massachusetts Gen. Hosp., Charlestown, MA, USA
  • fYear
    2013
  • fDate
    3-7 July 2013
  • Firstpage
    417
  • Lastpage
    420
  • Abstract
    We develop a particle filter algorithm to simultaneously estimate and track the instantaneous peak frequency, amplitude, and bandwidth of multiple concurrent non-stationary components of an EEG signal in the time-frequency domain. We use this method to characterize human EEG activity during anesthesia-induced unconsciousness.
  • Keywords
    electroencephalography; medical signal processing; neurophysiology; particle filtering (numerical methods); signal reconstruction; EEG data; EEG signal; anesthesia-induced unconsciousness; human EEG activity; instantaneous peak frequency; multiple concurrent nonstationary components; particle filter algorithm; simultaneous estimation; time-frequency domain; tracking nonstationary spectral peak structure; Bandwidth; Brain models; Electroencephalography; Frequency estimation; Particle filters; Time-frequency analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE
  • Conference_Location
    Osaka
  • ISSN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/EMBC.2013.6609525
  • Filename
    6609525