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| Author(s): |
Juliano Jinzenji Duque
Total Authors: 1
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| Document type: | Doctoral Thesis |
| Press: | Ribeirão Preto. |
| Institution: | Universidade de São Paulo (USP). Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (PCARP/BC) |
| Defense date: | 2017-08-09 |
| Examining board members: |
Luiz Otavio Murta Junior;
Odemir Martinez Bruno;
João Pereira Leite;
Ubiraci Pereira da Costa Neves;
Renato Tinós
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| Advisor: | Luiz Otavio Murta Junior |
| Abstract | |
Electroencephalography (EEG) is one of the evidences taken in the evaluation of surgical indication, in cases of patients with drug refractory epilepsy, which may help in locating the area responsible for the origin of epileptic seizures. Over the last few decades, in addition to the frequency bands that have traditionally been evaluated (up to about 40Hz), the EEG has attracted researchers also to higher frequency bands. Evidence has been found that high frequency oscillations (HFO), can be used as biomarkers of epilepsy. Many studies have been carried out in search of a better understanding about HFO, in order to make it feasible to use in clinical applications. However, nonlinear and complex features, which may contribute to the analysis of signals originating from biological systems, have not been investigated in this type of signals. This study proposed the investigation of features extracted from EEG signals with HFO of patients with refractory epilepsy, using nonlinear analysis methods. Symbolic Dynamics Analysis, Detrended Fluctuation Analysis (DFA), Multiscale Entropy (MSE) and qSDiff Analysis were applied to segments of intracranial EEG signals, sampled at 5kHz, from patients with refractory epilepsy, as well as some features-known simulated signals for comparison purposes. Results of the different investigated methods pointed out similar features between the analyzed EEG segments and the simulated series of Brownian noise, suggesting that EEG signals, in general, have a very smoothed profile, are nonstationary and exhibit long- range correlations. Evidence has also been raised that both HFO and the EEG segments where they are inserted have more regular patterns of variation and are less complex than EEG segments without HFO, suggesting the degradation of the physiological complexity of this brain region, which could be related to pathophysiological mechanisms of epilepsy. All the investigated methods suggested that nonlinear features and properties, related to the inherent complexity of EEG signals, may be useful in HFO analysis, mainly because of the evidence that these features change in HFOs when compared to the rest of the signal where they are and other signals without their presence. (AU) | |
| FAPESP's process: | 13/00922-5 - Evaluation of nonlinear analysis methods in electroencephalographic signals in the presence of High Frequency Oscillations (HFO) in patients with refractory epilepsy |
| Grantee: | Juliano Jinzenji Duque |
| Support Opportunities: | Scholarships in Brazil - Doctorate |