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Titolo:
Wavelet entropy: a new tool for analysis of short duration brain electrical signals
Autore:
Rosso, OA; Blanco, S; Yordanova, J; Kolev, V; Figliola, A; Schurmann, M; Basar, E;
Indirizzi:
Univ Buenos Aires, Inst Calculo, Fac Ciencias Exactas & Nat, RA-1428 Buenos Aires, DF, Argentina Univ Buenos Aires Buenos Aires DF Argentina RA-1428 Aires, DF, Argentina Bulgarian Acad Sci, Inst Physiol, BU-1113 Sofia, Bulgaria Bulgarian Acad Sci Sofia Bulgaria BU-1113 ysiol, BU-1113 Sofia, Bulgaria Med Univ Lubeck, Inst Physiol, D-23538 Lubeck, Germany Med Univ Lubeck Lubeck Germany D-23538 Physiol, D-23538 Lubeck, Germany TUBITAK Brain Dynam Res Unit, Ankara, Turkey TUBITAK Brain Dynam Res UnitAnkara Turkey nam Res Unit, Ankara, Turkey
Titolo Testata:
JOURNAL OF NEUROSCIENCE METHODS
fascicolo: 1, volume: 105, anno: 2001,
pagine: 65 - 75
SICI:
0165-0270(20010130)105:1<65:WEANTF>2.0.ZU;2-S
Fonte:
ISI
Lingua:
ENG
Soggetto:
TIME-FREQUENCY ANALYSIS; ELECTROENCEPHALOGRAM SERIES;
Keywords:
EEG, event-related potentials (ERP); visual evoked potential; time-frequency signal analysis; wavelet analysis; signal entropy;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Life Sciences
Citazioni:
33
Recensione:
Indirizzi per estratti:
Indirizzo: Rosso, OA Univ Buenos Aires, Inst Calculo, Fac Ciencias Exactas & Nat, Pabellon 2,Ciudad Univ, RA-1428 Buenos Aires, DF, Argentina Univ Buenos Aires Pabellon 2,Ciudad Univ Buenos Aires DF Argentina RA-1428
Citazione:
O.A. Rosso et al., "Wavelet entropy: a new tool for analysis of short duration brain electrical signals", J NEUROSC M, 105(1), 2001, pp. 65-75

Abstract

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 conceptsthat allow a better understanding of brain dynamics. Here, new method based on orthogonal discrete wavelet transform (ODWT) is applied. It takes as abasic element the ODWT of the EEG signal, and defines the relative waveletenergy, 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 physiologicalconditions 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. (C) 2001 Published by Elsevier Science B.V.

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Documento generato il 02/07/20 alle ore 21:58:58