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- W2892824083 abstract "Abstract For several decades, researchers are aiming for the detection of precursors of epileptic seizures. A system that is able to issue a warning about an impending seizure could dramatically improve the quality of life of affected patients. In this work, we apply multivariate autoregressive (MVAR) modeling to intracranial electroencephalography (iEEG) recordings of patients with therapy resistant epilepsy. As compared to our previous investigations, we studied the optimal model order of the autoregressive process as a feature for seizure prediction. In a statistical evaluation, we obtain significant results for 17 out of 20 patients." @default.
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- W2892824083 date "2018-09-01" @default.
- W2892824083 modified "2023-09-27" @default.
- W2892824083 title "Seizure Prediction by Multivariate Autoregressive Model Order Optimization" @default.
- W2892824083 doi "https://doi.org/10.1515/cdbme-2018-0094" @default.
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