| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 454918 | Computers & Electrical Engineering | 2014 | 8 Pages |
•A wavelet-based approach is applied to examine scale-invariant characteristics of epileptic EEGs.•The spectral exponents of epileptic EEGs corresponding to various states are different.•The wavelet bases used have an effect on the estimated spectral exponents.•The spectral exponent is shown to be related to the Hurst exponent.
There is evidence that biological and physiological systems including the brain exhibit can exhibit fractal characteristics that can be used to identify the state of the system. In this study, wavelet-based fractal analysis is used to examine self-similar or scale-invariant characteristics of intracranial EEG data in terms of the spectral exponent. The intracranial EEG data were recorded from subjects with epilepsy during non-seizure period and during epileptic seizure activity. From the computational results, it is observed that the self-similar or scale-invariant characteristics of the intracranial EEG data obtained during these two periods are significantly different. The actual value of the estimated spectral exponent depends on the wavelet bases used for the computations.
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