@inproceedings{93e0d9f8990542f2be24ea85ff2adf73,
title = "Hierarchal online temporal and spatial EEG seizure detection",
abstract = "Seizures affect a significant portion of the world's population and while a small proportion of the seizures are easy to detect, the vast majority are subtle enough to require the expertise of a neurologist. In this paper, we present a multifaceted computational approach to detecting the presence and locality of a seizure using Electroencephalography (EEG) signals. We test the proposed approach using a variety of signals and demonstrate the efficacy of the approach.",
keywords = "EEG, PSD, epilepsy, networks, nonspecific-patient detection, on-line detection, seizure",
author = "Amirsalar Mansouri and Sanjay Singh and Khalid Sayood",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Electro Information Technology, EIT 2017 ; Conference date: 14-05-2017 Through 17-05-2017",
year = "2017",
month = sep,
day = "27",
doi = "10.1109/EIT.2017.8053397",
language = "English (US)",
series = "IEEE International Conference on Electro Information Technology",
publisher = "IEEE Computer Society",
pages = "416--421",
booktitle = "2017 IEEE International Conference on Electro Information Technology, EIT 2017",
}