Wavelet entropy: A new tool for analysis of short duration brain electrical signals

Since traditional electrical brain signal analysis is mostly qualitative, the development of new quantitative methods is crucial for restricting the subjectivity in the study of brain signals. These methods are particularly fruitful when they are strongly correlated with intuitive physical concepts...

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Detalles Bibliográficos
Autores principales:	Blanco, Susana Alicia Ana, Figliola, María Alejandra
Publicado:	2001
Materias:	EEG, event-related potentials (ERP) Signal entropy Time-frequency signal analysis Visual evoked potential Wavelet analysis adult article auditory stimulation controlled study cortical synchronization electroencephalogram electroencephalography energy entropy event related potential evoked visual response frequency analysis human human experiment mathematical analysis normal human oscillation priority journal quantitative assay signal processing technique time volunteer waveform wavelet Adult Biological Clocks Brain Cortical Synchronization Electroencephalography Entropy Evoked Potentials Humans Models, Neurological Signal Processing, Computer-Assisted Time Factors
Acceso en línea:	https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01650270_v105_n1_p65_Rosso http://hdl.handle.net/20.500.12110/paper_01650270_v105_n1_p65_Rosso
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

id	paper:paper_01650270_v105_n1_p65_Rosso
record_format	dspace
spelling	paper:paper_01650270_v105_n1_p65_Rosso2023-06-08T15:14:34Z Wavelet entropy: A new tool for analysis of short duration brain electrical signals Blanco, Susana Alicia Ana Figliola, María Alejandra EEG, event-related potentials (ERP) Signal entropy Time-frequency signal analysis Visual evoked potential Wavelet analysis adult article auditory stimulation controlled study cortical synchronization electroencephalogram electroencephalography energy entropy event related potential evoked visual response frequency analysis human human experiment mathematical analysis normal human oscillation priority journal quantitative assay signal processing technique time volunteer waveform wavelet Adult Biological Clocks Brain Cortical Synchronization Electroencephalography Entropy Evoked Potentials Humans Models, Neurological Signal Processing, Computer-Assisted Time Factors Since traditional electrical brain signal analysis is mostly qualitative, the development of new quantitative methods is crucial for restricting the subjectivity in the study of brain signals. These methods are particularly fruitful when they are strongly correlated with intuitive physical concepts that allow a better understanding of brain dynamics. Here, new method based on orthogonal discrete wavelet transform (ODWT) is applied. It takes as a basic element the ODWT of the EEG signal, and defines the relative wavelet energy, the wavelet entropy (WE) and the relative wavelet entropy (RWE). The relative wavelet energy provides information about the relative energy associated with different frequency bands present in the EEG and their corresponding degree of importance. The WE carries information about the degree of order/disorder associated with a multi-frequency signal response, and the RWE measures the degree of similarity between different segments of the signal. In addition, the time evolution of the WE is calculated to give information about the dynamics in the EEG records. Within this framework, the major objective of the present work was to characterize in a quantitative way functional dynamics of order/disorder microstates in short duration EEG signals. For that aim, spontaneous EEG signals under different physiological conditions were analyzed. Further, specific quantifiers were derived to characterize how stimulus affects electrical events in terms of frequency synchronization (tuning) in the event related potentials. Copyright © 2001 Elsevier Science B.V. Fil:Blanco, S. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Figliola, A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2001 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01650270_v105_n1_p65_Rosso http://hdl.handle.net/20.500.12110/paper_01650270_v105_n1_p65_Rosso
institution	Universidad de Buenos Aires
institution_str	I-28
repository_str	R-134
collection	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic	EEG, event-related potentials (ERP) Signal entropy Time-frequency signal analysis Visual evoked potential Wavelet analysis adult article auditory stimulation controlled study cortical synchronization electroencephalogram electroencephalography energy entropy event related potential evoked visual response frequency analysis human human experiment mathematical analysis normal human oscillation priority journal quantitative assay signal processing technique time volunteer waveform wavelet Adult Biological Clocks Brain Cortical Synchronization Electroencephalography Entropy Evoked Potentials Humans Models, Neurological Signal Processing, Computer-Assisted Time Factors
spellingShingle	EEG, event-related potentials (ERP) Signal entropy Time-frequency signal analysis Visual evoked potential Wavelet analysis adult article auditory stimulation controlled study cortical synchronization electroencephalogram electroencephalography energy entropy event related potential evoked visual response frequency analysis human human experiment mathematical analysis normal human oscillation priority journal quantitative assay signal processing technique time volunteer waveform wavelet Adult Biological Clocks Brain Cortical Synchronization Electroencephalography Entropy Evoked Potentials Humans Models, Neurological Signal Processing, Computer-Assisted Time Factors Blanco, Susana Alicia Ana Figliola, María Alejandra Wavelet entropy: A new tool for analysis of short duration brain electrical signals
topic_facet	EEG, event-related potentials (ERP) Signal entropy Time-frequency signal analysis Visual evoked potential Wavelet analysis adult article auditory stimulation controlled study cortical synchronization electroencephalogram electroencephalography energy entropy event related potential evoked visual response frequency analysis human human experiment mathematical analysis normal human oscillation priority journal quantitative assay signal processing technique time volunteer waveform wavelet Adult Biological Clocks Brain Cortical Synchronization Electroencephalography Entropy Evoked Potentials Humans Models, Neurological Signal Processing, Computer-Assisted Time Factors
description	Since traditional electrical brain signal analysis is mostly qualitative, the development of new quantitative methods is crucial for restricting the subjectivity in the study of brain signals. These methods are particularly fruitful when they are strongly correlated with intuitive physical concepts that allow a better understanding of brain dynamics. Here, new method based on orthogonal discrete wavelet transform (ODWT) is applied. It takes as a basic element the ODWT of the EEG signal, and defines the relative wavelet energy, the wavelet entropy (WE) and the relative wavelet entropy (RWE). The relative wavelet energy provides information about the relative energy associated with different frequency bands present in the EEG and their corresponding degree of importance. The WE carries information about the degree of order/disorder associated with a multi-frequency signal response, and the RWE measures the degree of similarity between different segments of the signal. In addition, the time evolution of the WE is calculated to give information about the dynamics in the EEG records. Within this framework, the major objective of the present work was to characterize in a quantitative way functional dynamics of order/disorder microstates in short duration EEG signals. For that aim, spontaneous EEG signals under different physiological conditions were analyzed. Further, specific quantifiers were derived to characterize how stimulus affects electrical events in terms of frequency synchronization (tuning) in the event related potentials. Copyright © 2001 Elsevier Science B.V.
author	Blanco, Susana Alicia Ana Figliola, María Alejandra
author_facet	Blanco, Susana Alicia Ana Figliola, María Alejandra
author_sort	Blanco, Susana Alicia Ana
title	Wavelet entropy: A new tool for analysis of short duration brain electrical signals
title_short	Wavelet entropy: A new tool for analysis of short duration brain electrical signals
title_full	Wavelet entropy: A new tool for analysis of short duration brain electrical signals
title_fullStr	Wavelet entropy: A new tool for analysis of short duration brain electrical signals
title_full_unstemmed	Wavelet entropy: A new tool for analysis of short duration brain electrical signals
title_sort	wavelet entropy: a new tool for analysis of short duration brain electrical signals
publishDate	2001
url	https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01650270_v105_n1_p65_Rosso http://hdl.handle.net/20.500.12110/paper_01650270_v105_n1_p65_Rosso
work_keys_str_mv	AT blancosusanaaliciaana waveletentropyanewtoolforanalysisofshortdurationbrainelectricalsignals AT figliolamariaalejandra waveletentropyanewtoolforanalysisofshortdurationbrainelectricalsignals
_version_	1768545874918506496

Wavelet entropy: A new tool for analysis of short duration brain electrical signals

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