Analysis And Interpretation Of Electro-Encephalogram (EEG) Signals Under Various Physiological Conditions

Analysis And Interpretation Of Electro-Encephalogram (EEG) Signals Under Various Physiological Conditions

This research study discusses the application of chaotic parameters such as correlation dimension, Lyapunov exponent and Hurst exponent for studying EEG signals under different physiological conditions. EEG data sets obtained under conditions such as 1. Normal 2. Epilepsy 3. Different anesthetic dep...

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Main Author: Venkataraman, Lalitha
Format: Thesis
Published: 2010
Subjects:
RC1200 Sports Medicine
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spelling my-mmu-ep.35092012-04-18T03:57:47Z Analysis And Interpretation Of Electro-Encephalogram (EEG) Signals Under Various Physiological Conditions 2010-02 Venkataraman, Lalitha RC1200 Sports Medicine This research study discusses the application of chaotic parameters such as correlation dimension, Lyapunov exponent and Hurst exponent for studying EEG signals under different physiological conditions. EEG data sets obtained under conditions such as 1. Normal 2. Epilepsy 3. Different anesthetic depth levels 4. Alcoholic and non-alcoholic state are considered and chaos features are extracted. The extracted features are then used to classify the different physiological conditions using artificial neural network based classifier. 2010-02 Thesis http://shdl.mmu.edu.my/3509/ http://vlib.mmu.edu.my/diglib/login/dlusr/login.php masters University of Multimedia Research Library
institution Multimedia University
collection MMU Institutional Repository
topic RC1200 Sports Medicine
spellingShingle RC1200 Sports Medicine
Venkataraman, Lalitha
Analysis And Interpretation Of Electro-Encephalogram (EEG) Signals Under Various Physiological Conditions
description This research study discusses the application of chaotic parameters such as correlation dimension, Lyapunov exponent and Hurst exponent for studying EEG signals under different physiological conditions. EEG data sets obtained under conditions such as 1. Normal 2. Epilepsy 3. Different anesthetic depth levels 4. Alcoholic and non-alcoholic state are considered and chaos features are extracted. The extracted features are then used to classify the different physiological conditions using artificial neural network based classifier.
format Thesis
qualification_level Master's degree
author Venkataraman, Lalitha
author_facet Venkataraman, Lalitha
author_sort Venkataraman, Lalitha
title Analysis And Interpretation Of Electro-Encephalogram (EEG) Signals Under Various Physiological Conditions
title_short Analysis And Interpretation Of Electro-Encephalogram (EEG) Signals Under Various Physiological Conditions
title_full Analysis And Interpretation Of Electro-Encephalogram (EEG) Signals Under Various Physiological Conditions
title_fullStr Analysis And Interpretation Of Electro-Encephalogram (EEG) Signals Under Various Physiological Conditions
title_full_unstemmed Analysis And Interpretation Of Electro-Encephalogram (EEG) Signals Under Various Physiological Conditions
title_sort analysis and interpretation of electro-encephalogram (eeg) signals under various physiological conditions
granting_institution University of Multimedia
granting_department Research Library
publishDate 2010
_version_ 1747829513069264896

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