An approach to the processing of physiological signals is considered combining multifractal formalism with multiresolution wavelet analysis, which involves the transition from the original signals to sets of detail wavelet-coefficients related to different levels of resolution. This transition could expand the possibilities of multifractal analysis from the viewpoint of physiological interpretation of the results. In particular, changes in the singularity spectra due to variations in system behavior are associated with specific frequency regions, what simplifies their description and can provide a link between observed phenomena and changes in rhythms of electroencephalograms (EEG) or other physiological processes when the method is applied...
We review the central results concerning wavelet methods in multifractal analysis, which consists in...
Quantification of brain-heart interplay (BHI) has mainly been performed in the time and frequency do...
International audienceQuantification of brain-heart interplay (BHI) has mainly been performed in the...
An approach to the processing of physiological signals is considered combining multifractal formalis...
Recently, many lines of investigation in neuroscience and statistical physics have converged to rais...
Nonlinear and non-Gaussian analyses contribute to a comprehensive characterization of autonomic nerv...
We explore the degree to which concepts developed in statistical physics can be usefully applied to ...
Functional magnetic resonance imaging (fMRI) time series are investigated with a multifractal method...
Abstract: In data processing, the fundamental idea behind wavelets is to analyze according to scale,...
Abstract. Even under healthy, basal conditions, physiologic systems show erratic fluc-tuations resem...
International audienceAtrial fibrillation (AF) is a cardiac arrhythmia characterized by rapid and ir...
We review the central results concerning wavelet methods in multifractal analysis, which consists in...
Quantification of brain-heart interplay (BHI) has mainly been performed in the time and frequency do...
International audienceQuantification of brain-heart interplay (BHI) has mainly been performed in the...
An approach to the processing of physiological signals is considered combining multifractal formalis...
Recently, many lines of investigation in neuroscience and statistical physics have converged to rais...
Nonlinear and non-Gaussian analyses contribute to a comprehensive characterization of autonomic nerv...
We explore the degree to which concepts developed in statistical physics can be usefully applied to ...
Functional magnetic resonance imaging (fMRI) time series are investigated with a multifractal method...
Abstract: In data processing, the fundamental idea behind wavelets is to analyze according to scale,...
Abstract. Even under healthy, basal conditions, physiologic systems show erratic fluc-tuations resem...
International audienceAtrial fibrillation (AF) is a cardiac arrhythmia characterized by rapid and ir...
We review the central results concerning wavelet methods in multifractal analysis, which consists in...
Quantification of brain-heart interplay (BHI) has mainly been performed in the time and frequency do...
International audienceQuantification of brain-heart interplay (BHI) has mainly been performed in the...