Results in literature show that the convergence of the STLmax (Short Term Maximum Lyapunov Exponent) time series, extracted from intracranial EEG of patients affected by intractable temporal lobe epilepsy, is linked to the seizure onset. Moreover, the trend of the convergence allows for the automatic detection of the electrodes involved in the process leading to the seizure. ATSWA (Adaptive Threshold Seizure Warning Algorithm) is an advance seizure warning algorithm based on STLmax convergence.
Analysis of the Dynamics of Human Epileptic Seizures from Scalp EEG / Latella, A.; LA FORESTA, Fabio; Mammone, N; Morabito, Francesco Carlo; U., Aguglia; E., LE PIANE. - In: EPILEPSIA. - ISSN 0013-9580. - 50 (4):4(2009), pp. 184-184. (Intervento presentato al convegno European Congress on Epileptologyina tenutosi a Berlin, Germany nel September 21 - 25) [10.1111/j.1528-1167.2009.02063.x].
Analysis of the Dynamics of Human Epileptic Seizures from Scalp EEG
LA FORESTA, Fabio;Mammone N;MORABITO, Francesco Carlo;
2009-01-01
Abstract
Results in literature show that the convergence of the STLmax (Short Term Maximum Lyapunov Exponent) time series, extracted from intracranial EEG of patients affected by intractable temporal lobe epilepsy, is linked to the seizure onset. Moreover, the trend of the convergence allows for the automatic detection of the electrodes involved in the process leading to the seizure. ATSWA (Adaptive Threshold Seizure Warning Algorithm) is an advance seizure warning algorithm based on STLmax convergence.| File | Dimensione | Formato | |
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