Until the mid-1990s limitations in signal processing did not allow us to easily analyze frequency and temporal components of a given non-stationary signal at the same time. Wavelet transforms allow researchers to analyze the frequency components of a signal while not losing information about the time those components occur. In this work we apply these Wavelet techniques in the analysis of EEG data, particularly, to identify ultradian rhythms in rats. Our work presents a framework for computational analysis of EEG data for the detection of these ultradian rhythms.M.S.Includes bibliographical referencesby Dennis Ege
Wavelet transform has emerged over recent years as a favoured tool for the investigation of biomedic...
Contains fulltext : 77354.pdf (publisher's version ) (Closed access)Epileptic acti...
grantor: University of TorontoThis thesis explores the analysis and modeling of sensori-m...
EEG analysis is used as a tool for medical diagnosis of various diseases related to brain like epile...
EEG signals recorded by surface electrodes placed on the scalp can be thought as non- stationary sto...
We review time-frequency methods that can be useful in quantifying circadian and ultradian patterns ...
Wavelet packet decomposition is used to investigate the time-varying characteristics of clinical EEG...
EEG signals recorded by surface electrodes placed on the scalp can be thought as nonstationary stoch...
This book examines theoretical and applied aspects of wavelet analysis in neurophysics, describing i...
Using wavelet analysis we have detected the presence of chirps in seizure EEG signals recorded from ...
The continuous Morlet wavelet transform was used for the analysis of the time-frequency pattern of s...
In this work, we propose a modification of the wavelet oscillatory pattern method for analyzing ener...
The EEG is a non-invasive technique to study the brain and very useful in sleep analysis. The classi...
International audienceThis paper is aimed at presenting the two main classes of nonstationary signal...
Electroencephalography (EEG) is the recording of electrical activity along the scalp produced by the...
Wavelet transform has emerged over recent years as a favoured tool for the investigation of biomedic...
Contains fulltext : 77354.pdf (publisher's version ) (Closed access)Epileptic acti...
grantor: University of TorontoThis thesis explores the analysis and modeling of sensori-m...
EEG analysis is used as a tool for medical diagnosis of various diseases related to brain like epile...
EEG signals recorded by surface electrodes placed on the scalp can be thought as non- stationary sto...
We review time-frequency methods that can be useful in quantifying circadian and ultradian patterns ...
Wavelet packet decomposition is used to investigate the time-varying characteristics of clinical EEG...
EEG signals recorded by surface electrodes placed on the scalp can be thought as nonstationary stoch...
This book examines theoretical and applied aspects of wavelet analysis in neurophysics, describing i...
Using wavelet analysis we have detected the presence of chirps in seizure EEG signals recorded from ...
The continuous Morlet wavelet transform was used for the analysis of the time-frequency pattern of s...
In this work, we propose a modification of the wavelet oscillatory pattern method for analyzing ener...
The EEG is a non-invasive technique to study the brain and very useful in sleep analysis. The classi...
International audienceThis paper is aimed at presenting the two main classes of nonstationary signal...
Electroencephalography (EEG) is the recording of electrical activity along the scalp produced by the...
Wavelet transform has emerged over recent years as a favoured tool for the investigation of biomedic...
Contains fulltext : 77354.pdf (publisher's version ) (Closed access)Epileptic acti...
grantor: University of TorontoThis thesis explores the analysis and modeling of sensori-m...