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O A Rosso

Publications and source records attributed to O A Rosso.

10 recordsLinked to original sources
PubMed2006

EEG analysis using wavelet-based information tools.

Wavelet-based informational tools for quantitative electroencephalogram (EEG) record analysis are reviewed. Relative wavelet energies, wavelet entropies and wavelet statistical complexities are used in the characterization of scalp EEG records corresponding to secondary generalized tonic-clonic epileptic seizures. In particular, we show that the epileptic recruitment rhythm observed during seizure development is well described in terms of the relative wavelet energies. In addition, during the concomitant time-period the entropy diminishes while complexity grows. This is construed as evidence supporting the conjecture that an epileptic focus, for this kind of seizures, triggers a self-organized brain state characterized by both order and maximal complexity.

Adolescent↗
PubMed2005

The Australian EEG database.

The Australian EEG Database is a web-based de-identified searchable database of 18,500 EEG records recorded at a regional public hospital over an 11-year period. Patients range in age from a premature infant born at 24 weeks gestation, through to people aged over 90 years. This paper will describe the history of the database, the range of patients represented in the database, and the nature of the text-based and digital data contained in the database. Preliminary results of the first two studies undertaken using the database are presented. Plans for sharing data from the Australian EEG database with researchers are discussed. We anticipate that such data will be useful in not only helping to answer clinical questions but also in the field of mathematical modeling of the EEG.

Adolescent↗
PubMed2004

Analysis of wavelet-filtered tonic-clonic electroencephalogram recordings.

EEG signals obtained during tonic-clonic epileptic seizures can be severely contaminated by muscle and physiological noise. Heavily contaminated EEG signals are hard to analyse quantitatively and also are usually rejected for visual inspection by physicians, resulting in a considerable loss of collected information. The aim of this work was to develop a computer-based method of time series analysis for such EEGs. A method is presented for filtering those frequencies associated with muscle activity using a wavelet transform. One of the advantages of this method over traditional filtering is that wavelet filtering of some frequency bands does not modify the pattern of the remaining ones. In consequence, the dynamics associated with them do not change. After generation of a 'noise free' signal by removal of the muscle artifacts using wavelets, a dynamic analysis was performed using non-linear dynamics metric tools. The characteristic parameters evaluated (correlation dimension D2 and largest Lyapunov exponent lambda1) were compatible with those obtained in previous works. The average values obtained were: D2=4.25 and lambda1=3.27 for the pre-ictal stage; D2=4.03 and lambda1=2.68 for the tonic seizure stage; D2=4.11 and lambda1=2.46 for the clonic seizure stage.

Artifacts↗
PubMed2001

A transient dominance of theta ERP component characterizes passive auditory processing: evidence from a developmental study.

This study analyzed relationships among co-existent EEG frequency responses during passive auditory stimulus processing. By applying quantifiers based on wavelet entropy, it is demonstrated that a short-lasting ordering of the complex post-stimulus EEG signal occurs as a result of a transient synchronization in the theta frequency channel. Further, by using a developmental model it is shown that, independently of the frequency content of the background EEG and ERPs, a highly-ordered microstate in the ERP is always determined by theta frequency. Thus, transient dominance of synchronized theta oscillations may reflect an important functional mechanism subserving stimulus information processing.

Acoustic Stimulation↗
PubMed2001

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 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.

Adult↗
PubMed2001

Wavelet entropy in event-related potentials: a new method shows ordering of EEG oscillations.

In this work we show the application of a measure of entropy defined from the wavelet transform, namely the wavelet entropy (WS), to the study of event-related potentials (ERPs). WS was computed for ERPs recorded from nine healthy subjects with three different types of stimuli, among them target stimuli in a cognitive task. A significant decrease of entropy was correlated with the responses to target stimuli (P300), thus showing that these responses correspond to a more "ordered" state than the spontaneous EEG. Furthermore, we propose the WS as a quantitative measure for such transitions between EEG ("disordered state") and ERP ("ordered state").

Adult↗
PubMed1997

Searching for hidden information with Gabor Transform in generalized tonic-clonic seizures.

The analysis of generalized tonic clonic seizures is usually difficult with scalp EEG due to muscle artifact. We applied Gabor Transform to evaluate 20 seizures from 8 consecutive patients admitted for video-EEG monitoring. We studied the relative intensity ratios of alpha, theta and delta bands over time. In 14/20 events we found a significant decremental activity in the delta band at the onset of the seizure indicating that this is dominated by theta and alpha bands. We conclude that GT is a useful auxiliary tool in the analysis of ictal activity that sheds light on the underlying pathophysiological mechanisms.

Adult↗