A Multistage System for the Automated Detection of Epileptic Seizures in Neonatal Electroencephalography
| Autor: | Eli M. Mizrahi, Joyeeta Mitra, Periklis Y. Ktonas, Arun Thitai Kumar, Richard A. Hrachovy, Amit Mukherjee, Nicolaos B. Karayiannis, J.R. Glover, James D. Frost |
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| Rok vydání: | 2009 |
| Předmět: |
medicine.medical_specialty
Communication Neonatal intensive care unit Neonatal eeg medicine.diagnostic_test Physiology business.industry Context (language use) Audiology Electroencephalography Stage ii medicine.disease Epilepsy Neurology Physiology (medical) False detection medicine Neurology (clinical) business Delta activity |
| Zdroj: | Journal of Clinical Neurophysiology. 26:218-226 |
| ISSN: | 0736-0258 |
| DOI: | 10.1097/wnp.0b013e3181b2f29d |
| Popis: | This paper describes the design and test results of a three-stage automated system for neonatal EEG seizure detection. Stage I of the system is the initial detection stage and identifies overlapping 5-second segments of suspected seizure activity in each EEG channel. In stage II, the detected segments from stage I are spatiotemporally clustered to produce multichannel candidate seizures. In stage III, the candidate seizures are processed further using measures of quality and context-based rules to eliminate false candidates. False candidates because of artifacts and commonly occurring EEG background patterns such as bifrontal delta activity are also rejected. Seizures at least 10 seconds in duration are considered for reporting results. The testing data consisted of recordings of 28 seizure subjects (34 hours of data) and 48 nonseizure subjects (87 hours of data) obtained in the neonatal intensive care unit. The data were not edited to remove artifacts and were identical in every way to data normally processed visually. The system was able to detect seizures of widely varying morphology with an average detection sensitivity of almost 80% and a subject sensitivity of 96%, in comparison with a team of clinical neurophysiologists who had scored the same recordings. The average false detection rate obtained in nonseizure subjects was 0.74 per hour. |
| Databáze: | OpenAIRE |
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