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)