Seizure Detection: Interreader Agreement and Detection Algorithm Assessments Using a Large Dataset.

Mark L Scheuer¹, Scott B Wilson¹, Arun Antony², Gena Ghearing³, Alexandra Urban², Anto I Bagić²

¹Persyst Development Corporation, Solana Beach, California, U.S.A.

²University of Pittsburgh Comprehensive Epilepsy Center (UPCEC), University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, U.S.A.; and.

³Department of Neurology, University of Iowa, Iowa City, Iowa, U.S.A.

PubMed PMC DOI PDF

Abstract

PURPOSE: To compare the seizure detection performance of three expert humans and two computer algorithms in a large set of epilepsy monitoring unit EEG recordings. METHODS: One hundred twenty prolonged EEGs, 100 containing clinically reported EEG-evident seizures, were evaluated. Seizures were marked by the experts and algorithms. Pairwise sensitivity and false-positive rates were calculated for…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Create Free Account Sign In

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.