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dc.contributor.authorRana, Puneet
dc.contributor.authorLipor, John
dc.contributor.authorLee, Hyong
dc.contributor.authorVan Drongelen, Wim
dc.contributor.authorKohrman, Michael H.
dc.contributor.authorVan Veen, Barry D.
dc.date.accessioned2015-08-03T09:45:47Z
dc.date.available2015-08-03T09:45:47Z
dc.date.issued2012-01-18
dc.identifier.citationRana, P., Lipor, J., Hyong Lee, van Drongelen, W., Kohrman, M. H., & Van Veen, B. (2012). Seizure Detection Using the Phase-Slope Index and Multichannel ECoG. IEEE Transactions on Biomedical Engineering, 59(4), 1125–1134. doi:10.1109/tbme.2012.2184796
dc.identifier.issn00189294
dc.identifier.pmid22271828
dc.identifier.doi10.1109/TBME.2012.2184796
dc.identifier.urihttp://hdl.handle.net/10754/562142
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.
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.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3369624
dc.relation.urlhttp://europepmc.org/articles/pmc3369624?pdf=render
dc.rights(c) 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
dc.rightsThis file is an open access version redistributed from: http://europepmc.org/articles/pmc3369624?pdf=render
dc.subjectEpilepsy
dc.subjectmultichannel electrocorticogram (ECoG)
dc.subjectphase-slope index (PSI)
dc.subjectseizure detection
dc.subjectseizure evolution
dc.titleSeizure detection using the phase-slope index and multichannel ECoG
dc.typeArticle
dc.contributor.departmentElectrical Engineering Program
dc.identifier.journalIEEE Transactions on Biomedical Engineering
dc.identifier.pmcidPMC3369624
dc.eprint.versionPost-print
dc.contributor.institutionDepartment of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI 53715, United States
dc.contributor.institutionGoogle Inc., Mountain View, CA 94043, United States
dc.contributor.institutionDepartment of Pediatrics, Computation Institute, University of Chicago, Chicago, IL 60637, United States
dc.contributor.institutionDepartment of Pediatrics, Pediatric Epilepsy Center, University of Chicago, Chicago, IL 60637, United States
kaust.personLipor, John
refterms.dateFOA2020-07-01T13:25:45Z


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