@inproceedings{7eed208508a0423d9a7e91358388fc4d,
title = "Multi-channel EEG based neonatal seizure detection",
abstract = "A multi-channel method for patient specific and patient independent, EEG based neonatal seizure detection is presented. Two classifier configurations are proposed and tested, along with a number of classifier models. Existing methods for neonatal seizure detection have been empirical threshold based or based on a single EEG channel. The optimum patient specific classifier for EEG based neonatal seizure detection was found to be an Early Integration configuration employing a linear discriminant classifier model. This yielded a mean classification accuracy of 74.66\% for 11 neonatal records. The optimum patient independent classifier was an Early Integration configuration with a linear discriminant classifier model giving a mean accuracy of 72.81\%.",
author = "Greene, \{Barry R.\} and Reilly, \{Richard B.\} and Geraldine Boylan and \{De Chazal\}, Philip and Sean Connolly",
year = "2006",
doi = "10.1109/IEMBS.2006.260461",
language = "English",
isbn = "1424400325",
series = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4679--4684",
booktitle = "28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06",
address = "United States",
note = "28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06 ; Conference date: 30-08-2006 Through 03-09-2006",
}