Seizure detection using the phase-slope index and multichannel ECoG

Handle URI:
http://hdl.handle.net/10754/562142
Title:
Seizure detection using the phase-slope index and multichannel ECoG
Authors:
Rana, Puneet; Lipor, John; Lee, Hyong; Van Drongelen, Wim; Kohrman, Michael H.; Van Veen, Barry D.
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.
KAUST Department:
Electrical Engineering Program
Publisher:
Institute of Electrical and Electronics Engineers
Journal:
IEEE Transactions on Biomedical Engineering
Issue Date:
Apr-2012
DOI:
10.1109/TBME.2012.2184796
PubMed ID:
22271828
PubMed Central ID:
PMC3369624
Type:
Article
ISSN:
00189294
Sponsors:
Manuscript received May 16, 2011; revised October 31, 2011; accepted December 19, 2011. Date of publication January 18, 2012; date of current version March 21, 2012. This work was supported in part by the National Institutes of Health under award R21EB009749 and the Dr. Ralph and Marian Falk Medical Research Trust. Asterisk indicates corresponding author.
Additional Links:
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3369624
Appears in Collections:
Articles; Electrical Engineering Program

Full metadata record

DC FieldValue Language
dc.contributor.authorRana, Puneeten
dc.contributor.authorLipor, Johnen
dc.contributor.authorLee, Hyongen
dc.contributor.authorVan Drongelen, Wimen
dc.contributor.authorKohrman, Michael H.en
dc.contributor.authorVan Veen, Barry D.en
dc.date.accessioned2015-08-03T09:45:47Zen
dc.date.available2015-08-03T09:45:47Zen
dc.date.issued2012-04en
dc.identifier.issn00189294en
dc.identifier.pmid22271828en
dc.identifier.doi10.1109/TBME.2012.2184796en
dc.identifier.urihttp://hdl.handle.net/10754/562142en
dc.description.abstractDetection 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.en
dc.description.sponsorshipManuscript received May 16, 2011; revised October 31, 2011; accepted December 19, 2011. Date of publication January 18, 2012; date of current version March 21, 2012. This work was supported in part by the National Institutes of Health under award R21EB009749 and the Dr. Ralph and Marian Falk Medical Research Trust. Asterisk indicates corresponding author.en
dc.publisherInstitute of Electrical and Electronics Engineersen
dc.relation.urlhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3369624en
dc.subjectEpilepsyen
dc.subjectmultichannel electrocorticogram (ECoG)en
dc.subjectphase-slope index (PSI)en
dc.subjectseizure detectionen
dc.subjectseizure evolutionen
dc.titleSeizure detection using the phase-slope index and multichannel ECoGen
dc.typeArticleen
dc.contributor.departmentElectrical Engineering Programen
dc.identifier.journalIEEE Transactions on Biomedical Engineeringen
dc.identifier.pmcidPMC3369624en
dc.contributor.institutionDepartment of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI 53715, United Statesen
dc.contributor.institutionGoogle Inc., Mountain View, CA 94043, United Statesen
dc.contributor.institutionDepartment of Pediatrics, Computation Institute, University of Chicago, Chicago, IL 60637, United Statesen
dc.contributor.institutionDepartment of Pediatrics, Pediatric Epilepsy Center, University of Chicago, Chicago, IL 60637, United Statesen
kaust.authorLipor, Johnen

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