The global framework of this paper is the synchronization analysis in EEG recordings. Two main objectives are pursued: the evaluation of the synchronization estimation for lateralization purposes in epileptic EEGs and the evaluation of the effect of the preprocessing (artifact and noise cancelling by blind source separation, wavelet denoising and classification) on the synchronization analysis. We propose a new global synchronization index, based on the classical cross power spectrum, estimated for each cerebral hemisphere. After preprocessing, the proposed index is able to correctly lateralize the epileptic zone in over 90% of the cases
The nonlinear nature of phase coupling enables rich and context-sensitive interactions that characte...
Multivariate time series analysis is of primary importance for the estimation of starting time of ep...
Complex biological systems such as the human brain can be expected to be inherently nonlinear and he...
The global framework of this paper is the synchronization analysis in EEG recordings. Two main objec...
The global framework of this paper is the synchronization analysis in EEG recordings. Two main objec...
International audienceObjective: The objective of this work is the determination of the lateralizati...
The application of non-linear signal analysis techniques to biomedical data is key to improve our kn...
Epilepsy is a persistent and recurring neurological condition in a community of brain neurons that r...
Summarization: Epilepsy is one of the most common brain disorders and may result in brain dysfunctio...
AbstractWe investigate the emergence of synchronization in two groups of oscillators; one group acts...
There are various methods to measure the value of synchronization of signals. These methods usually ...
A longstanding challenge in epilepsy research and practice is the need to classify synchronization p...
The question whether information extracted from the electroencephalogram ~EEG! of epilepsy patients ...
A longstanding challenge in epilepsy research and practice is the need to classify synchronization p...
The electroencephalogram (EEG) is the essential clinical examination for the diagnosis, the definiti...
The nonlinear nature of phase coupling enables rich and context-sensitive interactions that characte...
Multivariate time series analysis is of primary importance for the estimation of starting time of ep...
Complex biological systems such as the human brain can be expected to be inherently nonlinear and he...
The global framework of this paper is the synchronization analysis in EEG recordings. Two main objec...
The global framework of this paper is the synchronization analysis in EEG recordings. Two main objec...
International audienceObjective: The objective of this work is the determination of the lateralizati...
The application of non-linear signal analysis techniques to biomedical data is key to improve our kn...
Epilepsy is a persistent and recurring neurological condition in a community of brain neurons that r...
Summarization: Epilepsy is one of the most common brain disorders and may result in brain dysfunctio...
AbstractWe investigate the emergence of synchronization in two groups of oscillators; one group acts...
There are various methods to measure the value of synchronization of signals. These methods usually ...
A longstanding challenge in epilepsy research and practice is the need to classify synchronization p...
The question whether information extracted from the electroencephalogram ~EEG! of epilepsy patients ...
A longstanding challenge in epilepsy research and practice is the need to classify synchronization p...
The electroencephalogram (EEG) is the essential clinical examination for the diagnosis, the definiti...
The nonlinear nature of phase coupling enables rich and context-sensitive interactions that characte...
Multivariate time series analysis is of primary importance for the estimation of starting time of ep...
Complex biological systems such as the human brain can be expected to be inherently nonlinear and he...