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. 2009 Sep;120(9):1648-57.
doi: 10.1016/j.clinph.2009.07.002. Epub 2009 Jul 25.

A fuzzy rule-based system for epileptic seizure detection in intracranial EEG

A Aarabi  1 , R Fazel-Rezai, Y Aghakhani
Affiliations

A fuzzy rule-based system for epileptic seizure detection in intracranial EEG

A Aarabi et al. Clin Neurophysiol. 2009 Sep.

Abstract

Objective: We present a method for automatic detection of seizures in intracranial EEG recordings from patients suffering from medically intractable focal epilepsy.

Methods: We designed a fuzzy rule-based seizure detection system based on knowledge obtained from experts' reasoning. Temporal, spectral, and complexity features were extracted from IEEG segments, and spatio-temporally integrated using the fuzzy rule-based system for seizure detection. A total of 302.7h of intracranial EEG recordings from 21 patients having 78 seizures was used for evaluation of the system.

Results: The system yielded a sensitivity of 98.7%, a false detection rate of 0.27/h, and an average detection latency of 11s. There was only one missed seizure. Most of false detections were caused by high-amplitude rhythmic activities. The results from the system correlate well with those from expert visual analysis.

Conclusion: The fuzzy rule-based seizure detection system enabled us to deal with imprecise boundaries between interictal and ictal IEEG patterns.

Significance: This system may serve as a good seizure detection tool with high sensitivity and low false detection rate for monitoring long-term IEEG.

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