TY  - JOUR
  - Thomas, E; Temko, A; Lightbody, G; Marnane, W. P. and Boylan, G
  - 2010
  - July
  - Physiological Measurement
  - Gaussian mixture models for classification of neonatal seizures using EEG
  - Validated
  - ()
  - Neonatal EEG seizure detection Gaussian mixture models EPILEPTIC SEIZURES SYSTEM ALGORITHM FEATURES INFANTS
  - 31
  - 7
  - 1047
  - 1064
  - A real-time neonatal seizure detection system is proposed based on a Gaussian mixture model classifier. The system includes feature transformation techniques and classifier output postprocessing. The detector was evaluated on a database of 20 patients with 330 h of recordings. A detailed analysis of the choice of parameters for the detector is provided. A mean good detection rate of 79% was obtained with only 0.5 false detections per hour. Athorough review of all misclassified events was performed, from which a number of patterns causing false detections were identified.
  - United Kingdom
  - 0967-3334
  - http://iopscience.iop.org/0967-3334/
  - DOI 10.1088/0967-3334/31/7/013
  - Science Foundation Ireland
  - Science Foundation Ireland (SFI/05/PICA/1836), Wellcome Trust (085249/Z/08/Z)
DA  - 2010/07
ER  - 

@article{V43334157,
   = {Thomas, E and  Temko, A and  Lightbody, G and  Marnane, W. P. and Boylan, G},
   = {2010},
   = {July},
   = {Physiological Measurement},
   = {Gaussian mixture models for classification of neonatal seizures using EEG},
   = {Validated},
   = {()},
   = {Neonatal EEG seizure detection Gaussian mixture models EPILEPTIC SEIZURES SYSTEM ALGORITHM FEATURES INFANTS},
   = {31},
   = {7},
  pages = {1047--1064},
   = {{A real-time neonatal seizure detection system is proposed based on a Gaussian mixture model classifier. The system includes feature transformation techniques and classifier output postprocessing. The detector was evaluated on a database of 20 patients with 330 h of recordings. A detailed analysis of the choice of parameters for the detector is provided. A mean good detection rate of 79% was obtained with only 0.5 false detections per hour. Athorough review of all misclassified events was performed, from which a number of patterns causing false detections were identified.}},
   = {United Kingdom},
  issn = {0967-3334},
   = {http://iopscience.iop.org/0967-3334/},
   = {DOI 10.1088/0967-3334/31/7/013},
   = {Science Foundation Ireland},
   = {Science Foundation Ireland (SFI/05/PICA/1836), Wellcome Trust (085249/Z/08/Z)},
  source = {IRIS}
}