Abstract:
:The ability to accurately forecast seizures could significantly improve the quality of life of patients with drug-refractory epilepsy. Prediction capabilities rely on the adequate identification of seizure activity precursors from electroencephalography recordings. Although a long list of features has been proposed, none of these is able to independently characterize the brain states during transition to a seizure. This work assessed the feasibility of using the bispectrum, an advanced signal processing technique based on higher order statistics, as a precursor of seizure activity. Quantitative features were extracted from the bispectrum and passed through two statistical tests to check for significant differences between preictal and interictal recordings. Results showed statistically significant differences (p < 0.05) between preictal and interictal states using all bispectrum-extracted features. We used normalized bispectral entropy, normalized bispectral squared entropy, and mean of magnitude as inputs to a 5-layer multilayer perceptron classifier and achieved respective held-out test accuracies of 78.11%, 72.64%, and 73.26%.
journal_name
Sci Repjournal_title
Scientific reportsauthors
Bou Assi E,Gagliano L,Rihana S,Nguyen DK,Sawan Mdoi
10.1038/s41598-018-33969-9subject
Has Abstractpub_date
2018-10-19 00:00:00pages
15491issue
1issn
2045-2322pii
10.1038/s41598-018-33969-9journal_volume
8pub_type
杂志文章abstract::Plasmodiophora brassicae causes clubroot disease in cruciferous. In this report, lipid droplets were observed in the resting spores of P. brassicae. 295 lipid droplet-associated proteins were identified and categorized into nine groups. Transcriptome analysis of these proteins during three different zoosporic stages r...
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