The University of Southampton
University of Southampton Institutional Repository

Epilepsy detection using detrended fluctuation analysis

Epilepsy detection using detrended fluctuation analysis
Epilepsy detection using detrended fluctuation analysis
Epilepsy is a disorder of the central nervous system characterized by the loss of consciousness and convulsions. If some early warning signal of an upcoming seizure (diagnosis of preictal period) could be detected, proper treatment could be applied to the patient to help prevent the seizure. In this articles, detrended fluctuation analysis (DFA) has been introduced and used to extract the DFA feature from EEG signal. DFA is a scaling analysis method that provides a simple quantitative parameter to represent the correlation properties of a signal, we come to 100% separation of Normal, Preictal, and Ictal states of the brain
978-1-4244-3728-3
235-240
IEEE
Shalbaf, R.
97742966-009b-4936-a8e6-99fa7896855f
Hosseini, P.T.
47511a4b-5adc-4e93-9d2a-46e3016c87fb
Shalbaf, R.
97742966-009b-4936-a8e6-99fa7896855f
Hosseini, P.T.
47511a4b-5adc-4e93-9d2a-46e3016c87fb

Shalbaf, R. and Hosseini, P.T. (2009) Epilepsy detection using detrended fluctuation analysis. In Proceedings of the IEEE International Conference on Wavelet Analysis and Pattern Recognition. IEEE. pp. 235-240 . (doi:10.1109/ICWAPR.2009.5207454).

Record type: Conference or Workshop Item (Paper)

Abstract

Epilepsy is a disorder of the central nervous system characterized by the loss of consciousness and convulsions. If some early warning signal of an upcoming seizure (diagnosis of preictal period) could be detected, proper treatment could be applied to the patient to help prevent the seizure. In this articles, detrended fluctuation analysis (DFA) has been introduced and used to extract the DFA feature from EEG signal. DFA is a scaling analysis method that provides a simple quantitative parameter to represent the correlation properties of a signal, we come to 100% separation of Normal, Preictal, and Ictal states of the brain

This record has no associated files available for download.

More information

Published date: 2009
Venue - Dates: IEEE International Conference on Wavelet Analysis and Pattern Recognition, Baoding, China, 2009-01-01

Identifiers

Local EPrints ID: 192049
URI: http://eprints.soton.ac.uk/id/eprint/192049
ISBN: 978-1-4244-3728-3
PURE UUID: 476210d5-7f1a-4af8-8b30-52e44d600b5d

Catalogue record

Date deposited: 29 Jun 2011 11:33
Last modified: 14 Mar 2024 03:48

Export record

Altmetrics

Contributors

Author: R. Shalbaf
Author: P.T. Hosseini

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×