Hierarchal online temporal and spatial EEG seizure detection

Amirsalar Mansouri; Sanjay Singh; Khalid Sayood

doi:10.1109/EIT.2017.8053397

Hierarchal online temporal and spatial EEG seizure detection

Amirsalar Mansouri, Sanjay Singh, Khalid Sayood

Department of Neurology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

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.

Original language	English (US)
Title of host publication	2017 IEEE International Conference on Electro Information Technology, EIT 2017
Publisher	IEEE Computer Society
Pages	416-421
Number of pages	6
ISBN (Electronic)	9781509047673
DOIs	https://doi.org/10.1109/EIT.2017.8053397
State	Published - Sep 27 2017
Event	2017 IEEE International Conference on Electro Information Technology, EIT 2017 - Lincoln, United States Duration: May 14 2017 → May 17 2017

Other

Other	2017 IEEE International Conference on Electro Information Technology, EIT 2017
Country	United States
City	Lincoln
Period	5/14/17 → 5/17/17

All Science Journal Classification (ASJC) codes

Computer Science Applications
Information Systems
Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/EIT.2017.8053397

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Mansouri, A, Singh, S & Sayood, K 2017, Hierarchal online temporal and spatial EEG seizure detection. in 2017 IEEE International Conference on Electro Information Technology, EIT 2017., 8053397, IEEE Computer Society, pp. 416-421, 2017 IEEE International Conference on Electro Information Technology, EIT 2017, Lincoln, United States, 5/14/17. https://doi.org/10.1109/EIT.2017.8053397

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