Development of an AR-pole statistic for ECoG seizure detection

Maribeth Bozek-Kuzmicki, Steven L. Weinstein, George Benke, Steven J. Schiff

Research output: Contribution to journalConference article

3 Citations (Scopus)

Abstract

We consider the problem of epileptic seizure detection and focus localization from ECoG signals. ECoG are subdural recordings of electric potentials collected by invasively placing a grid on the surface of the brain. A statistic based on an autoregressive (AR) model has been developed to aid in seizure detection and localization. Specifically, we build a statistic based on the location of three dominant poles (obtained from the AR polynomial) relative to the unit circle. This statistic has produced results that are in agreement with findings by clinical ECoG readers for five patient cases examined.

Original languageEnglish (US)
Pages (from-to)935-936
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

Poles
Seizures
Statistics
Epilepsy
Brain
Polynomials
Electric potential

All Science Journal Classification (ASJC) codes

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

Cite this

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Development of an AR-pole statistic for ECoG seizure detection. / Bozek-Kuzmicki, Maribeth; Weinstein, Steven L.; Benke, George; Schiff, Steven J.

In: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, Vol. 17, No. 2, 01.12.1995, p. 935-936.

Research output: Contribution to journalConference article

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N2 - We consider the problem of epileptic seizure detection and focus localization from ECoG signals. ECoG are subdural recordings of electric potentials collected by invasively placing a grid on the surface of the brain. A statistic based on an autoregressive (AR) model has been developed to aid in seizure detection and localization. Specifically, we build a statistic based on the location of three dominant poles (obtained from the AR polynomial) relative to the unit circle. This statistic has produced results that are in agreement with findings by clinical ECoG readers for five patient cases examined.

AB - We consider the problem of epileptic seizure detection and focus localization from ECoG signals. ECoG are subdural recordings of electric potentials collected by invasively placing a grid on the surface of the brain. A statistic based on an autoregressive (AR) model has been developed to aid in seizure detection and localization. Specifically, we build a statistic based on the location of three dominant poles (obtained from the AR polynomial) relative to the unit circle. This statistic has produced results that are in agreement with findings by clinical ECoG readers for five patient cases examined.

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