Comput. Biol. Med. - Early detection of epileptic seizures based on parameter identification of neural mass model.

Tópicos

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{ method(2212) result(1239) propos(1039) }

Resumo

Physiologically based models are attractive for seizure detection, as their parameters can be explicitly related to neurological mechanisms. We propose an early seizure detection algorithm based on parameter identification of a neural mass model. The occurrence of a seizure is detected by analysing the time shift of key model parameters. The algorithm was evaluated against the manual scoring of a human expert on intracranial EEG samples from 16 patients suffering from different types of epilepsy. Results suggest that the algorithm is best suited for patients suffering from temporal lobe epilepsy (sensitivity was 95.0% ? 10.0% and false positive rate was 0.20 ? 0.22 per hour).

Resumo Limpo

physiolog base model attract seizur detect paramet can explicit relat neurolog mechan propos earli seizur detect algorithm base paramet identif neural mass model occurr seizur detect analys time shift key model paramet algorithm evalu manual score human expert intracrani eeg sampl patient suffer differ type epilepsi result suggest algorithm best suit patient suffer tempor lobe epilepsi sensit fals posit rate per hour

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