Search PubMed⌕ Search

Biomedical subjects

K Eftaxias

Publications and source records attributed to K Eftaxias.

10 recordsLinked to original sources

Preseismic electromagnetic signals in terms of complexity.

There is a recent thesis in the literature that an important organization of a physical system precedes a catastrophic event. In this context, one can search for signatures that imply the transition from a normal state to a main catastrophic event (e.g., earthquake). Experimental techniques are thus useful in corroborating theories from observed data. For example, recent results indicate that preseismic electromagnetic time series contain information characteristic of an ensuing earthquake event. Hereby, we attempt to demonstrate that an easily computable complexity measure, such as T-complexity or approximate entropy, gives evidence of state changes leading to the point of global instability. The appearance of a precatastrophic state is characterized by significant lower complexity in terms of T-complexity and approximate entropy. The present study confirms the conclusions of previous works based on an independent linear fractal spectral analysis. This convergence between nonlinear and linear analysis provides a more reliable detection concerning the emergence of the last phase of the earthquake preparation process. More precisely, we claim that our results suggest an important principle: significant complexity decrease and accession of persistency in electromagnetic (EM) time series can be confirmed at the tail of the preseismic EM emission, which could be used as diagnostic tools for the Earth's impending crust failure. Direct laboratory and field experimental data as well as theoretical arguments support the conclusions of the present analysis.

Journal Article↗

Fractal spectral analysis of pre-epileptic seizures in terms of criticality.

The analysis of pre-epileptic seizure through EEG (electroencephalography) is an important issue for epilepsy diagnosis. Currently, there exist some methods derived from the dynamics to analyse the pre-epileptic EEG data. It is still necessary to create a novel method to better fit and explain the EEG data for making sense of the seizures' predictability. In this paper, a fractal wavelet-based spectral method is proposed and applied to analyse EEG recordings from rat experiments. Three types of patterns are found from the 12 experiments; moreover three typical cases corresponding to the three types of seizures are sorted out and analysed in detail by using the new method. The results indicate that this method can reveal the characteristic signs of an approaching seizure, which includes the emergence of long-range correlation, the decrease of anti-persistence behaviour with time and the decrease of the fractal dimension. The pre-seizure features and their implications are further discussed in the framework of the theory of criticality. We suggest that an epileptic seizure could be considered as a generalized kind of "critical phenomenon", culminating in a large event that is analogous to a kind of "critical point". We also emphasize that epileptic event emergence is a non-repetitive process, so the critical interpretation meets a certain number of cases.

Algorithms↗