Gaussian mixture models for classification of neonatal seizures using EEG.
Physiol Meas
; 31(7): 1047-64, 2010 Jul.
Article
em En
| MEDLINE
| ID: mdl-20585148
ABSTRACT
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. A thorough review of all misclassified events was performed, from which a number of patterns causing false detections were identified.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Convulsões
/
Eletroencefalografia
/
Modelos Neurológicos
Tipo de estudo:
Prognostic_studies
Limite:
Humans
/
Newborn
Idioma:
En
Ano de publicação:
2010
Tipo de documento:
Article