Literature DB >> 1370137

Long-term EEG-video-audio monitoring: computer detection of focal EEG seizure patterns.

F Pauri1, F Pierelli, G E Chatrian, W W Erdly.   

Abstract

Twelve individuals with medically refractory partial seizures had undergone EEG-video-audio (EVA) monitoring over 1-15 (mean 10.5) days. We selectively reexamined available 15-channel EEGs (video-cassettes) totaling 461 h and containing 253 EEG focal seizures. Computer analysis (CA) of these bipolar records was performed using a mimetic method of seizure detection at 6 successive computer settings. We determined the computer parameters at which this method correctly detected a reasonably large percentage of seizures (81.42%) while generating an acceptable rate of false positive results (5.38/h). These parameters were adopted as the default setting for identifying focal EEG seizure patterns in all subsequent long-term bipolar scalp and sphenoidal recordings. Factors hindering or facilitating automatic seizure identification are discussed. It is concluded that on-line computer detection of focal EEG seizure patterns by this method offers a satisfactory alternative to and represents a distinct improvement over the extremely time consuming and fatiguing off-line fast visual review (FVR). Combining CA with seizure signaling (SS) by the patients and other observers increased the correct detections to 85.38% CA is best used in conjunction with SS.

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Mesh:

Year:  1992        PMID: 1370137     DOI: 10.1016/0013-4694(92)90175-h

Source DB:  PubMed          Journal:  Electroencephalogr Clin Neurophysiol        ISSN: 0013-4694


  5 in total

1.  Seizure detection in adult ICU patients based on changes in EEG synchronization likelihood.

Authors:  A J C Slooter; E M Vriens; F S S Leijten; J J Spijkstra; A R J Girbes; A C van Huffelen; C J Stam
Journal:  Neurocrit Care       Date:  2006       Impact factor: 3.210

2.  Classification of Focal and Non Focal Epileptic Seizures Using Multi-Features and SVM Classifier.

Authors:  N Sriraam; S Raghu
Journal:  J Med Syst       Date:  2017-09-02       Impact factor: 4.460

3.  Detection of Epileptic Seizures Using Phase-Amplitude Coupling in Intracranial Electroencephalography.

Authors:  Kohtaroh Edakawa; Takufumi Yanagisawa; Haruhiko Kishima; Ryohei Fukuma; Satoru Oshino; Hui Ming Khoo; Maki Kobayashi; Masataka Tanaka; Toshiki Yoshimine
Journal:  Sci Rep       Date:  2016-05-05       Impact factor: 4.379

Review 4.  Automatic Computer-Based Detection of Epileptic Seizures.

Authors:  Christoph Baumgartner; Johannes P Koren; Michaela Rothmayer
Journal:  Front Neurol       Date:  2018-08-09       Impact factor: 4.003

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

Authors:  Mark L Scheuer; Scott B Wilson; Arun Antony; Gena Ghearing; Alexandra Urban; Anto I Bagić
Journal:  J Clin Neurophysiol       Date:  2021-09-01       Impact factor: 2.590

  5 in total

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