Feature-based detection of epileptic seizures using ECoG recordings and a PAM model

Elizabeth S. Hughes, William D. Gaillard, Garry M. Jacyna, Steven Schiff

Research output: Contribution to journalConference article

2 Citations (Scopus)

Abstract

This paper develops a detection scheme for identifying seizure onset using single channel electrocorticograms recorded from intractable epilepsy patients. A statistic which measures changes in the peaks of the autocovariance function of a signal is developed based upon a pulse amplitude modulation model. This method is useful both for detecting seizure onset and for localizing the seizure focus within the cortical tissue by comparing data collected from multiple electrodes.

Original languageEnglish (US)
Pages (from-to)933-934
Number of pages2
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume17
Issue number2
StatePublished - Dec 1 1995
EventProceedings of the 1995 IEEE Engineering in Medicine and Biology 17th Annual Conference and 21st Canadian Medical and Biological Engineering Conference. Part 2 (of 2) - Montreal, Can
Duration: Sep 20 1995Sep 23 1995

Fingerprint

Pulse amplitude modulation
Epilepsy
Seizures
Statistics
Tissue
Electrodes

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Cite this

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Feature-based detection of epileptic seizures using ECoG recordings and a PAM model. / Hughes, Elizabeth S.; Gaillard, William D.; Jacyna, Garry M.; Schiff, Steven.

In: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, Vol. 17, No. 2, 01.12.1995, p. 933-934.

Research output: Contribution to journalConference article

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AU - Gaillard, William D.

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