Mandatory Fields

Authors

Ahmad, A., Temko, A., Marnane, W.P., Boylan, G. and Lightbody, G.

Conference Title

IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP -2014

Title of Paper

Grading Brain Injury in Neonatal EEG using SVM and Supervector Kernal

Year

2014

Month

May

Status

Published

Peer Reviewed

Times Cited

()

Optional Fields

Keywords

Editors

Start Page

5894

End Page

5898

Location

Florence, Italy

Start Date

04-MAY-15

End Date

09-MAY-15

Abstract

Brain injury at the time of birth could lead to severe neurological dysfunction at an older age. Grading the brain injury in the early hours after birth could help doctors determine a prompt and reliable treatment. This work presents an automated neonatal EEG grading system based on a crossdisciplinary method of using Support Vector Machine and supervectors, initially developed for speaker identification. The EEG is classified into one of the four grades of neonatal brain injury. The preliminary results show promising performance and are an improvement on the previously published results.

Funded By

URL

DOI Link

10.1109/ICASSP.2014.6854734

Grant Details

Funding Body

Science Foundation Ireland

Grant Details

12/RC/2272