Grading hypoxic-ischemic encephalopathy severity in neonatal EEG using GMM supervectors and the support vector machine.

Journal: Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology

PMID: 26093932

OBJECTIVE: This work presents a novel automated system to classify the severity of hypoxic-ischemic encephalopathy (HIE) in neonates using EEG.

Rehan Ahmed

Neonatal Brain Research Group, Irish Centre for Fetal and Neonatal Translational Research (INFANT), Ireland; Department of Electrical and Electronics Engineering, University College Cork, Ireland. Electronic address: rehan@eleceng.ucc.ie.
Andriy Temko

Neonatal Brain Research Group, Irish Centre for Fetal and Neonatal Translational Research (INFANT), Ireland; Department of Electrical and Electronics Engineering, University College Cork, Ireland.
William Marnane

Neonatal Brain Research Group, Irish Centre for Fetal and Neonatal Translational Research (INFANT), Ireland; Department of Electrical and Electronics Engineering, University College Cork, Ireland.
Gordon Lightbody

Neonatal Brain Research Group, Irish Centre for Fetal and Neonatal Translational Research (INFANT), Ireland; Department of Electrical and Electronics Engineering, University College Cork, Ireland.
Geraldine Boylan

Neonatal Brain Research Group, Irish Centre for Fetal and Neonatal Translational Research (INFANT), Ireland; Department of Pediatrics and Child Health, University College Cork, Ireland.

Electroencephalography Female Humans Hypoxia-Ischemia, Brain Infant, Newborn Male Support Vector Machine

View on PubMed Access via DOI PubMed (26093932)