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Detection of rhythmic discharges in newborn EEG signals

Mohseni, H. R ; Sharif University of Technology | 2006

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  1. Type of Document: Article
  2. DOI: 10.1109/IEMBS.2006.260892
  3. Publisher: 2006
  4. Abstract:
  5. This paper presents a scalp electroencephalogram (EEG) rhythmic pattern detection scheme based on neural networks. Rhythmic discharges detection is applicable to the majority of seizures seen in newborns, and is listed as detecting 90% of all the seizures. In this approach some features based on various methods are extracted and compared by a modified multilayer neural network in order to find rhythmic discharges. Statistical performance comparison with seizure detection schemes of Gotman et al. and Liu et al. is performed. © 2006 IEEE
  6. Keywords:
  7. Feature extraction ; Multilayer neural networks ; Neonatal monitoring ; Pattern recognition ; Statistical methods ; Newborn EEG signals ; Rhythmic discharges detection ; Seizures ; Statistical performance ; Electroencephalography
  8. Source: 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06, New York, NY, 30 August 2006 through 3 September 2006 ; 2006 , Pages 6577-6580 ; 05891019 (ISSN); 1424400325 (ISBN); 9781424400324 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/4030603