Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Anticipating epileptic seizures through the analysis of EEG
  synchronization as a data classification problem   Epilepsy is a neurological disorder arising from anomalies of the electrical
activity in the brain, affecting about 0.5--0.8\% of the world population.
Several studies investigated the relationship between seizures and brainwave
synchronization patterns, pursuing the possibility of identifying interictal,
preictal, ictal and postictal states. In this work, we introduce a graph-based
model of the brain interactions developed to study synchronization patterns in
the electroencephalogram (EEG) signals. The aim is to develop a
patient-specific approach, also for a real-time use, for the prediction of
epileptic seizures' occurrences. Different synchronization measures of the EEG
signals and easily computable functions able to capture in real-time the
variations of EEG synchronization have been considered. Both standard and
ad-hoc classification algorithms have been developed and used. Results on scalp
EEG signals show that this simple and computationally viable processing is able
to highlight the changes in the synchronization corresponding to the preictal
state.

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The categories of this paper are: eess
30
The categories of this paper are: q-alg
6
The categories of this paper are: astro-ph
20
The categories of this paper are: acc-phys
37
The categories of this paper are: supr-con
27
The categories of this paper are: comp-gas
35
The categories of this paper are: mtrl-th
33
The categories of this paper are: plasm-ph
0
The categories of this paper are: hep-ph
32
The categories of this paper are: atom-ph
31
The categories of this paper are: ao-sci
15
The categories of this paper are: nucl-ex
2
The categories of this paper are: math
9
The categories of this paper are: nlin
11
The categories of this paper are: hep-lat
21
The categories of this paper are: adap-org