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Brain Dynamics Based Automated Epileptic Seizure Detection

Abstract Approximately 1% of the world population suffers from epilepsy. Continuous long-term electroencephalographic (EEG) monitoring is the gold-standard for recording epileptic seizures and assisting in the diagnosis and treatment of patients with epilepsy. However, this process still requires that seizures are visually detected and marked by experienced and trained electroencephalographers. The motivation for the development of an automated seizure detection algorithm in this research was to assist physicians in such a laborious, time consuming and expensive task. Seizures in the EEG vary in duration (seconds to minutes), morphology and severity (clinical to subclinical, occurrence rate) within the same patient and across patients. The task of s... (more)
Created Date 2012
Contributor Venkataraman, Vinay (Author) / Jassemidis, Leonidas (Advisor) / Spanias, Andreas (Advisor) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Subject Biomedical engineering / Health care management / EEG / Epilepsy / Lyapunov exponent / Seizure detection / Teager Energy
Type Masters Thesis
Extent 64 pages
Language English
Reuse Permissions All Rights Reserved
Note M.S. Electrical Engineering 2012
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis