| Seizure detection using the phase-slope index and multichannel ECoG. | |
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MedLine Citation:
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PMID: 22271828 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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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. |
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Authors:
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Puneet Rana; John Lipor; Hyong Lee; Wim van Drongelen; Michael H Kohrman; Barry Van Veen |
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Publication Detail:
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Type: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't Date: 2012-01-18 |
Journal Detail:
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Title: IEEE transactions on bio-medical engineering Volume: 59 ISSN: 1558-2531 ISO Abbreviation: IEEE Trans Biomed Eng Publication Date: 2012 Apr |
Date Detail:
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Created Date: 2012-03-22 Completed Date: 2012-07-23 Revised Date: 2013-04-03 |
Medline Journal Info:
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Nlm Unique ID: 0012737 Medline TA: IEEE Trans Biomed Eng Country: United States |
Other Details:
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Languages: eng Pagination: 1125-34 Citation Subset: IM |
Affiliation:
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Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI 53715, USA. rana.puneet@gmail.com |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Adolescent Algorithms* Child Child, Preschool Diagnosis, Computer-Assisted / methods* Electroencephalography / methods* Female Humans Infant Infant, Newborn Male Pattern Recognition, Automated / methods* Reproducibility of Results Seizures / diagnosis* Sensitivity and Specificity |
| Grant Support | |
ID/Acronym/Agency:
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R21 EB009749/EB/NIBIB NIH HHS; R21EB009749/EB/NIBIB NIH HHS |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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