2001
DOI: 10.1016/s1388-2457(01)00522-3
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Using simulated neuronal cell models for detection of epileptic seizures in foramen ovale and scalp EEG

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Cited by 33 publications
(22 citation statements)
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“…The time points corresponding to ictal onset and offset were identified using a method developed by Schindler et al [18]. The time series was divided into 6 second moving windows with an overlap of 5.75 seconds and the z-score of the time series within each window was obtained in order to normalize the variance of the channels.…”
Section: Methodsmentioning
confidence: 99%
“…The time points corresponding to ictal onset and offset were identified using a method developed by Schindler et al [18]. The time series was divided into 6 second moving windows with an overlap of 5.75 seconds and the z-score of the time series within each window was obtained in order to normalize the variance of the channels.…”
Section: Methodsmentioning
confidence: 99%
“…S i (t) is an appropriate characteristic of epileptiform EEG because it increases for both high amplitude slow, but also low amplitude fast activities, as are typically observed at the onset and during intracranially recorded seizures. 4 In a second step, S i (t) was normalised to …”
Section: Methodsmentioning
confidence: 99%
“…Up to now, several investigations based on nonlinear time series analysis have been carried out on intracranial and surface EEG data with promising results [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][22][23][24][25][26]. Table 1 summarizes the achievements of seizure prediction methods developed to date.…”
Section: Introductionmentioning
confidence: 99%