Seizure detection using the phase-slope index and multichannel ECoG

Puneet Rana, John Lipor, Hyong Lee, Wim Van Drongelen, Michael H. Kohrman, Barry D. Van Veen

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

Detection and analysis of epileptic seizures is of clinical and research interest. We propose a novel seizure detection and analysis scheme based on the phase-slope index (PSI) of directed influence applied to multichannel electrocorticogram data. The PSI metric identifies increases in the spatio-temporal interactions between channels that clearly distinguish seizure from interictal activity. We form a global metric of interaction between channels and compare this metric to a threshold to detect the presence of seizures. The threshold is chosen based on a moving average of recent activity to accommodate differences between patients and slow changes within each patient over time. We evaluate detection performance over a challenging population of five patients with different types of epilepsy using a total of 47 seizures in nearly 258 h of recorded data. Using a common threshold procedure, we show that our approach detects all of the seizures in four of the five patients with a false detection rate less than two per hour. A variation on the global metric is proposed to identify which channels are strong drivers of activity in each patient. These metrics are computationally efficient and suitable for real-time application. © 2006 IEEE.
Original languageEnglish (US)
Pages (from-to)1125-1134
Number of pages10
JournalIEEE Transactions on Biomedical Engineering
Volume59
Issue number4
DOIs
StatePublished - Jan 18 2012

ASJC Scopus subject areas

  • Biomedical Engineering

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