Application of Embedded Dynamic Mode Decomposition on Epileptic Data for Seizure Prediction

Simple item page
dc.contributor.advisorAazhang, Behnaam
dc.creatorErfanian Taghvayi, Negar
dc.date.accessioned2020-06-05T17:27:53Z
dc.date.available2020-06-05T17:27:53Z
dc.date.created2019-12
dc.date.issued2020-05-27
dc.date.submittedDecember 2019
dc.date.updated2020-06-05T17:27:53Z
dc.description.abstractThe underlying spatiotemporal mechanism that leads to the formation of seizures in the brain has been an interesting topic for decades. Different techniques have been proposed to extract the dynamics of epileptic recordings that are involved in seizure formation. Methods have been used to measure the synchrony between two or more epileptic recordings. These techniques are often model-based or suffer from poor time-frequency resolution. In this project, we introduce a data-driven toolbox called the Dynamic Mode Decomposition (DMD) with time-delay embedding to extract the underlying spatio-temporal dynamics of seizure formation. These techniques will enable us to focus on similarities among seizures in our attempt to better understand, detect, and predict seizures. The inferred information on the underlying dynamics of an epileptic system are essential in terms of improving the capability of stimulation-based treatments of epileptic patients.
dc.format.mimetypeapplication/pdf
dc.identifier.citationErfanian Taghvayi, Negar. "Application of Embedded Dynamic Mode Decomposition on Epileptic Data for Seizure Prediction." (2020) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/108777">https://hdl.handle.net/1911/108777</a>.
dc.identifier.urihttps://hdl.handle.net/1911/108777
dc.language.isoeng
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.
dc.subjectDynamic Mode Decomposition
dc.subjectEpilepsy
dc.subjectSeizure Prediction
dc.subjectLinear Embedding
dc.titleApplication of Embedded Dynamic Mode Decomposition on Epileptic Data for Seizure Prediction
dc.typeThesis
dc.type.materialText
thesis.degree.departmentElectrical and Computer Engineering
thesis.degree.disciplineEngineering
thesis.degree.grantorRice University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
ERFANIANTAGHVAYI-DOCUMENT-2019.pdf
Size:
1.84 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 2 of 2
No Thumbnail Available
Name:
PROQUEST_LICENSE.txt
Size:
5.85 KB
Format:
Plain Text
Description:
Download
No Thumbnail Available
Name:
LICENSE.txt
Size:
2.62 KB
Format:
Plain Text
Description:
Download
Collections
Rice University Electronic Theses and Dissertations