@inbook{b30e1b88f1e74e138990e8fdf40e8fcd,
title = "Grading brain injury in neonatal EEG using SVM and supervector kernel",
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 cross-disciplinary 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.",
author = "Rehan Ahmed and Andriy Temko and William Marnane and Geraldine Boylan and Gordon Lightbody",
year = "2014",
doi = "10.1109/ICASSP.2014.6854734",
language = "English",
isbn = "9781479928927",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "5894--5898",
booktitle = "2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014",
address = "United States",
note = "2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 ; Conference date: 04-05-2014 Through 09-05-2014",
}