Wavelet transforms for electroencephalographic spike and seizure detection

Steven Schiff, John G. Milton

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations


The application of wavelet transforms (WT) to experimental data from the nervous system has been hindered by the lack of a straightforward method to handle noise. A noise reduction technique, developed recently for use in wavelet cluster analysis in cosmology and astronomy, is here adapted for electroencephalographic (EEG) time-series data. Noise is filtered using control surrogate data sets generated from randomized aspects of the original time-series. In this study, WT were applied to EEG data from human patients undergoing brain mapping with implanted subdural electrodes for the localization of epileptic seizure foci. EEG data in 1D were analyzed from individual electrodes, and 2D data from electrode grids. These techniques are a powerful means to identify epileptic spikes in such data, and offer a method to identity the onset and spatial extent of epileptic seizure foci. The method is readily applied to the detection of structure in stationary and non-stationary time-series from a variety of physical systems.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsWilliam L. Ditto
PublisherPubl by Society of Photo-Optical Instrumentation Engineers
Number of pages7
ISBN (Print)0819412856
StatePublished - Dec 1 1993
EventChaos in Biology and Medicine - San Diego, CA, USA
Duration: Jul 12 1993Jul 13 1993

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


OtherChaos in Biology and Medicine
CitySan Diego, CA, USA

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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