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

Rosso, Osvaldo A.; Blanco, Susana; Yordanova, Juliana; Kolev, Vasil; Figliola, A.; Schürmann, Martin; Başar, Erol

doi:10.1016/s0165-0270(00)00356-3

Cited by 750 publications

(492 citation statements)

References 17 publications

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“…To establish how the visual marking of HFA background was related to a quantitative measure of rhythmicity, we implemented an automatic classifier based on the wavelet entropy of the EEG (Rosso et al, 2001). Wavelet entropy measures the rhythmicity of the signal, independently of its amplitude.…”

Section: Automatic Classification Of Hfa Backgroundmentioning

confidence: 99%

Continuous High Frequency Activity: A peculiar SEEG pattern related to specific brain regions

Melani

Zelmann

Mari

et al. 2013

Clinical Neurophysiology

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Objective-While visually marking the high frequency oscillations in the stereo-EEG of epileptic patients, we observed a continuous/semicontinuous activity in the ripple band (80-250 Hz), which we defined continuous High Frequency Activity (HFA). We aim to analyze in all brain regions the occurrence and significance of this particular pattern.Methods-Twenty patients implanted in mesial temporal and neocortical areas were studied. One minute of slow-wave sleep was reviewed. The background was classified as continuous/ semicontinuous, irregular, or sporadic based on the duration of the fast oscillations. Each channel was classified as inside/outside the seizure onset zone (SOZ) or a lesion.Results-The continuous/semicontinuous HFA occurred in 54 of the 790 channels analyzed, with a clearly higher prevalence in hippocampus and occipital lobe. No correlation was found with the SOZ or lesions. In the occipital lobe the continuous/semicontinuous HFA was present independently of whether eyes were open or closed. Conclusions-We describe what appears to be a new physiological High Frequency Activity, independent of epileptogenicity, present almost exclusively in the hippocampus and occipital cortex but independent of the alpha rhythm.Significance-The continuous HFA may be an intrinsic characteristic of specific brain regions, reflecting a particular type of physiological neuronal activity.

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Section: Automatic Classification Of Hfa Backgroundmentioning

confidence: 99%

Continuous High Frequency Activity: A peculiar SEEG pattern related to specific brain regions

Melani

Zelmann

Mari

et al. 2013

Clinical Neurophysiology

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“…The wavelet analysis is a method which relies on the introduction of an appropriate basis and a characterization of the signal by the distribution of amplitude in the basis (Rosso et al 2001). If the wavelet required can form a proper orthogonal basis, it has the advantage that an arbitrary function can be uniquely decomposed and the decomposition can be inverted (Aldroubi and Unser 1996;Mallat 1999).…”

Section: Wavelet Transformmentioning

confidence: 99%

“…In the present work, we employ orthogonal cubic spline functions as mother wavelets. That is because the cubic spline functions are symmetric and combine in a suitable proportion smoothness with numerical advantages (Rosso et al 2001). Now, they have become a recommendable tool for representing natural signals.…”

Section: Wavelet Transformmentioning

confidence: 99%

Multi-scale order recurrence quantification analysis of EEG signals evoked by manual acupuncture in healthy subjects

Wang

Bian

et al. 2012

Cogn Neurodyn

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To explore the effects of manual acupuncture (MA) on brain activities, we design an experiment that acupuncture at acupoint ST36 of right leg with four different frequencies to obtain electroencephalograph (EEG) signals. Many studies have demonstrated that the complexity of EEG can reflect the states of brain function, so we propose to adopt order recurrence quantification analysis combined with discrete wavelet transform, to analyze the dynamical characteristics of different EEG rhythms under acupuncture, further to explore the effects of MA on the complexity of brain activities from multi-scale point of view. By analyzing the complexity of five EEG rhythms, it is found that the complexity of delta rhythm during acupuncture is lower than before acupuncture, and for alpha rhythm that is higher, but for beta, theta and gamma rhythms there are no obvious changes. All of those effects are especially obvious during acupuncture with frequency of 200 times/min. Furthermore, the determinism extracted from delta, alpha and gamma rhythms can be regarded as a characteristic parameter to distinguish the state acupuncture at 200 times/min and the state before acupuncture. These results can provide a theoretical support for selecting appropriate acupuncture frequency for patients in clinical, and the proposed methods have the potential of exploring the effects of acupuncture on brain activities.

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“…The RWE was obtained by continuous wavelet transform coefficients, with an approach differing from the previous analysis given in [15][16][17]. Wavelet entropy has been evaluated by using continuous wavelet transform coefficients as in the previous works [18,19].…”

Section: Relative Wavelet Energymentioning

confidence: 99%

“…The total wavelet entropy (WE) is a measure which gives information about the complexity of the signal. The formulation of Shannon WE is defined in [15] as…”

Section: Wavelet Entropymentioning

confidence: 99%

Continuous time wavelet entropy of auditory evoked potentials

Cek

Özgören

Savacı

2010

Computers in Biology and Medicine

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a b s t r a c tIn this paper, the continuous time wavelet entropy (CTWE) of auditory evoked potentials (AEP) has been characterized by evaluating the relative wavelet energies (RWE) in specified EEG frequency bands. Thus, the rapid variations of CTWE due to the auditory stimulation could be detected in post-stimulus time interval. This approach removes the probability of missing the information hidden in short time intervals. The discrete time and continuous time wavelet based wavelet entropy variations were compared on non-target and target AEP data. It was observed that CTWE can also be an alternative method to analyze entropy as a function of time.

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

Cited by 750 publications

References 17 publications

Continuous High Frequency Activity: A peculiar SEEG pattern related to specific brain regions

Continuous High Frequency Activity: A peculiar SEEG pattern related to specific brain regions

Multi-scale order recurrence quantification analysis of EEG signals evoked by manual acupuncture in healthy subjects

Continuous time wavelet entropy of auditory evoked potentials

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